Luminous Landscape Forum
Raw & Post Processing, Printing => Colour Management => Topic started by: torger on March 08, 2015, 06:31:03 am
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I'm continuing my project to drill deeper into camera profiling and is now trying to find out what the "current best" in camera profiling is.
It seems like camera profiling is a narrow genre with not so much software available at all, and there's a lot of old half-dead software out there too. I simply doesn't look like a vital software genre.
First let's sum up raw converters that support camera profiling:
* Adobe Lightroom (DNG Profiles = DCP)
* Phase One Capture One (ICC profile)
* Hasselblad Phocus (ICC profile)
* DxO Optics (ICC profile)
* Iridient Developer (ICC profile, seems also to have limited DNG profile support)
* Raw Photo Processor (ICC profile)
* RawTherapee (DNG profile and ICC profile)
* Corel Aftershot Pro (previously called Bibble, ICC profile)
* Photo Ninja (built-in format(?), has profiling built-in)
When it comes to ICC profiles it varies between software how the raw converters want them, Capture One wants ~1.8 gamma in them for example, but the profiling workflow usually fixes that automatically. However it seems like some ICC camera profiling software only supports a subset of the ICC raw converters. The DNG profile format has the advantage of being more well-defined.
Most profiling software seems to be sold together with a test target, like QPCard, Coloreyes, X-Rite.
When it comes it comes to DNG profiles (DCP), there's:
* Adobe DNG Profile Editor which only support MacBeth 24 patch colorchecker
* X-Rite has bundled software with their test targets, 24 patch colorchecker and the larger digital colorchecker SG (~96 patches)
* QPCard 35 patches with bundled software QPCalibration
* Datacolor SpyderCheckr 48 patches bundled software
For ICC (many same as the above as many support both DNG and ICC):
* X-Rite Profile Maker 5 (discontinued, ie interestingly enough X-Rite only supports DNG profiles nowadays)
* Datacolor SpyderCheckr, only Hasselblad Phocus
* Integrated Color Coloreyes, bundled with a 500 patch target
* QPCard
* Argyll, free open source supports most commercial targets and also custom-made
Photo Ninja raw converter seems to be a special case with built-in camera profiling support for the X-rite targets both the small 24 patch and the larger SG target.
Strangely enough it seems like today there's only Argyll that supports custom third-party targets, and there's no DNG profile maker that does it. Is this really the case or has I missed something? Lasersoft is selling a target without software and I doubt that they would if Argyll would be the only alternative to use it. Well, there's X-Rite Ipublish Pro2 which supports IT8 targets from Lasersoft (and Wolf Faust), but afaik it's the transparent targets for scanners rather than the reflective for cameras. For cameras it semes like X-rite only supports DNG and their own targets. Please correct me if wrong. X-rite's web site is a disaster and it's almost impossible to find any information of how their products work.
Only looking at the specs it seems like Coloreyes is the most serious product with it's bundled 500 individually measured target, but it can't do DNG profiles. For DNG profiles the current best seems to be X-rite Colorchecker SG. With Argyll you can use custom targets and most of the commercial ones, the weakness is that it's harder to use and supports only ICC and only "reproduction" type of profiles, ie there's no support for doing subjective hand-tuning like most(?) commercial profiling software do.
What I mainly miss here is DNG profile software that can do custom targets.
Another question is how valuable it really is to have many patches, or if a 24 patch profile will be as good. A limitation with test targets is that only a small gamut of what the camera can capture will be tested. A reflective target can't do very dark colors or very saturated colors, so even if you have a massive amount of patches you will sample only a smaller part of the camera's gamut. If you're going to do reproduction work of artwork it won't be a problem as the artwork will have limited gamut too, but for an all-around profile it might be a problem. I guess camera manufacturers use monochromators or some other sort of active target to get around this issue, but there seems to be no commercially available calibration solution with monochromators or the new multi-channel LEDs (10-22 channels full-spectrum programmable).
Is there any established "truth" of what the best commercially available camera profiling product is?
I think there are two aspects, 1) how accurate profiles can be made (for reproduction work) and 2) how subjectively-tunable it is for generic profile making. For example one may want to have a profile without hue-twists to make it more predictable, one may want to increase color separation in a certain color range, or reduce it, or one may want to add more saturation to the shadows etc.
And please add to the lists above (or correct if you find any errors)
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An additional question, anyone who knows how camera manufacturers does it in-house? With a monochromator you could measure the CFA response, like the examples shown here: https://spectralestimation.wordpress.com/data/
If you have the CFA response you could get CIE XYZ coordinates for them using the color matching functions, and voila you would have a matrix profile, but that would still only be approximate in practice as matrix-only profiles are. Maybe there's some better way to derive camera color from the CFA response? Or perhaps you would still combine the monochromator result with a reflective test target?
I think it would be wonderful if there was a color model where the only thing you would need to do is to measure the CFA response curves and then you could design any profile you'd like from that. I don't know if it's possible though.
A monochromator is not a cheap product though, but you can get a 300-800nm mini-chrom for about $1200... so if one could make high end stuff with it I would consider getting one, but I guess there's no software.
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First things first. Is the raw converter going to expect a DNG camera profile or ICC profile? HUGE differences here both in terms of the sanity of moving forward, how the profile is applied and on what data (hugely a factor) then you can go down the ICC camera profile rabbit hole if necessary and start with targets and software.
TIP: this is potentially a time consuming and frustrating affair depending on what your answer for question 1.
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* Datacolor SpyderCheckr 48 patches bundled software
not again... they do not make dcp profiles, they make ACR/LR recipes (HSL tab)
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Is the raw converter going to expect a DNG camera profile or ICC profile?
code can be written to handle both
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* X-Rite has bundled software with their test targets, 24 patch colorchecker and the larger digital colorchecker SG (~96 patches)
XRite OEM software that makes dcp profiles only works with 24 patch target... or with subset of colorchecker SG representing 24 patches similar to xrite passport
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* Iridient Developer (ICC profile, seems also to have limited DNG profile support)
somebody published an exchange between him (somebody) and Brian Griffith about DNG support in Iridient (that was pre v3, but still) - search here...
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but there seems to be no commercially available calibration solution with monochromators or the new multi-channel LEDs (10-22 channels full-spectrum programmable).
argyll can do and it is not worse than commercial, no ?
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What I mainly miss here is DNG profile software that can do custom targets.
a decent software developer like you can write some kind of icc to dcp translator, granted it is not a replacement of full dcp functionality, but still.
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code can be written to handle both
You're missing the point. One works really well, deals with raw scene referred data to do the job. The other doesn't. Kind of like the question: I have a DSLR, should I shoot raw or JPEG and you answering, well there are camera systems that allow both. Yes, but the differences in the approach and results is hugely different!
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You're missing the point. One works really well, deals with raw scene referred data to do the job. The other doesn't.
you are totally clueless... icc profiling can be done with raw data, that was pointed to you (yes, to you personally) many times in this forum - just use rawdigger in your workflow... and that is not to mention that argyll can work with monochromator data for example, while no publicly available dcp solution can... and you can do flatfielding again with raw digger for icc profiling workflow - you can't with dcp ones (publicly available... now I believe that all that Adobe has internally - but primitive tools for dcp profiling available to hoi polloi are what they are - primitive)
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you are totally clueless...
As are the ICC apparently:
Using ICC profiles with digital camera images
http://www.color.org/whitepapers.xalter
Again to the OP, if you want to dig yourself into a color management rabbit hole, outside of copy work and very controlled shooting, you do want to look into ICC camera profiling. If you use a raw converter that supports DNG profiles, your life will be far easier.
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An additional question, anyone who knows how camera manufacturers does it in-house? With a monochromator you could measure the CFA response, like the examples shown here: https://spectralestimation.wordpress.com/data/
If you have the CFA response you could get CIE XYZ coordinates for them using the color matching functions, and voila you would have a matrix profile, but that would still only be approximate in practice as matrix-only profiles are. Maybe there's some better way to derive camera color from the CFA response? Or perhaps you would still combine the monochromator result with a reflective test target?
I think it would be wonderful if there was a color model where the only thing you would need to do is to measure the CFA response curves and then you could design any profile you'd like from that. I don't know if it's possible though.
A monochromator is not a cheap product though, but you can get a 300-800nm mini-chrom for about $1200... so if one could make high end stuff with it I would consider getting one, but I guess there's no software.
Do you know the spectral response in (HSL) for the RGGB filters used to filter photons onto the sensor that produces a monochromatic (grayscale) response as voltage readings per each pixel site that has to be reconstructed and encoded by software?
Back in my illustration days when I was learning to use dyes and pigmented paint by visually examining the level of intensity each paint medium reflected back basic primary hues lit by daylight, I notice some were far more intense than others especially Doctor Martin dyes VS Windsor Newton watercolors.
I even asked Brian Griffith several years ago how he determined the intensity of the RGGB filters in order to build each ICC camera profile and he stated the majority of sensors (Sony?) out of Japan (engineers he spoke with) told him were close to NTSC color gamut. If you have a display that is exactly like NTSC gamut examine its individual full saturation of 255 Red, Green & Blue purities. Also examine gradients from full saturation to white and black, measure that and build a profile.
I tried to assign NTSC to a tiff converted to ProPhotoRGB out of Iridient Developer back then and it didn't work out so well. I gave up and just accepted what Adobe's DNG profiling did to my color which renders most of my images quite close to how it appears in front of my camera.
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The original way of applying an ICC profile was to convert to TIFF from the raw converter (using the raw converter's default color) and then handle color management outside the raw converter entirely. This is where the bad reputation of ICC profiles comes from.
However any raw converter with ICC support allows exporting a TIFF before color correction, ie what you get is the raw RGB channels with white balance applied, and possibly a curve. This is just as for DNG raw scene referred data, so there's not that big a difference as some seem to think. The DNG profile format is a lot easier to understand though, has floating point natively supported, and has more flexibility with dual illuminants and a pre-exposure and post-exposure LUT.
Writing an ICC to DNG Profile converter software is indeed possible and I'm thinking about doing that, but what you will have to do then is to specify which raw converter the ICC profile was made for and the profile converter (PC) must know how that raw converter pre-processes the image data before it puts it through the ICC profile, which is not the same for all raw converters. When knowing the PC would create a synthetic raw image with "all colors", pre-process it in the same way, put it through the ICC profile and save the result. Then it would run the same synthetic raw image through DNG pre-processing procedure and generate a DNG profile which produces as similar result as possible as the ICC profile. It's pretty massive work though, and seems to be a really long way to get a DNG profile, ie first profile using an ICC capable software like Capture One with Argyll and your custom target, and then convert that to a DNG profile to use in Lightroom.
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The original way of applying an ICC profile was to convert to TIFF from the raw converter (using the raw converter's default color) and then handle color management outside the raw converter entirely. This is where the bad reputation of ICC profiles comes from.
However any raw converter with ICC support allows exporting a TIFF before color correction, ie what you get is the raw RGB channels with white balance applied, and possibly a curve. This is just as for DNG raw scene referred data, so there's not that big a difference as some seem to think. The DNG profile format is a lot easier to understand though, has floating point natively supported, and has more flexibility with dual illuminants and a pre-exposure and post-exposure LUT.
Writing an ICC to DNG Profile converter software is indeed possible and I'm thinking about doing that, but what you will have to do then is to specify which raw converter the ICC profile was made for and the profile converter (PC) must know how that raw converter pre-processes the image data before it puts it through the ICC profile, which is not the same for all raw converters. When knowing the PC would create a synthetic raw image with "all colors", pre-process it in the same way, put it through the ICC profile and save the result. Then it would run the same synthetic raw image through DNG pre-processing procedure and generate a DNG profile which produces as similar result as possible as the ICC profile. It's pretty massive work though, and seems to be a really long way to get a DNG profile, ie first profile using an ICC capable software like Capture One with Argyll and your custom target, and then convert that to a DNG profile to use in Lightroom.
Is there a question in there or are you just describing the hurdles of ICC vs DNG camera profiling no one seems to be concerned about? What are you trying to solve here? I haven't seen anything better and easier than what I'm currently using. I've put ICC camera profiling behind me because frankly I don't like the results it produces.
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If you have the CFA response you could get CIE XYZ coordinates for them using the color matching functions, and voila you would have a matrix profile
Hmm... I'm not sure if this is possible, I was thinking wrong when I wrote that stuff above. I tried to just make an integration, and sure that did not look good and of course it won't as I then just get the XYZ coordinates for the filter curve of red green and blue. I guess there should be some mathematical way to go from CFA curves to RGB primaries in XYZ coordinates, but I haven't figured it out. If someone knows how, please let me know :-).
I guess you could write software that runs through a large number of virtual test patches (each test patch a spectrum curve) against those filter curves and profile in the same way as you do with a physical test target, but here with any saturation you'd like. May that is how manufacturers do it?
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Is there a question in there or are you just describing the hurdles of ICC vs DNG camera profiling no one seems to be concerned about? What are you trying to solve here? I haven't seen anything better and easier than what I'm currently using. I've put ICC camera profiling behind me because frankly I don't like the results it produces.
No I was just describing the hurdles in there. As I'm writing an article about various aspects of camera profiling I'm drilling down as deep as I can into the subject. I've worked quite extensively with color management as a software developer, so I know quite a lot already, but still hungry for more :-). When it comes to camera profiling I've only made basic 24 patch color checker DNG profiles so far, and they've worked fine for my purposes but there's many unanswered questions. When I recently made printer profile experiments I came to the conclusion that at least 900 patches was sort of required for a high end profile. Can a camera profile be good with only 24 patches is then a question I'd like to investigate together with many more.
With ICC vs DNG it's much about which raw software you like. If you rather use Capture One than Lightroom and like to profile your camera you have to make an ICC profile because that is what Capture One supports. To make a complete article I must cover both DNG and ICC profiles.
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Hmm... I'm not sure if this is possible, I was thinking wrong when I wrote that stuff above. I tried to just make an integration, and sure that did not look good and of course it won't as I then just get the XYZ coordinates for the filter curve of red green and blue. I guess there should be some mathematical way to go from CFA curves to RGB primaries in XYZ coordinates, but I haven't figured it out. If someone knows how, please let me know :-).
I guess you could write software that runs through a large number of virtual test patches (each test patch a spectrum curve) against those filter curves and profile in the same way as you do with a physical test target, but here with any saturation you'd like. May that is how manufacturers do it?
You left out the most influential aspect of your workflow and that being demosiaicing algrorithms which if you don't line 'em up right with your curves and matrices can skew the overall "petina" of the image making it look kinda' funky but in a way you can't put your finger on it.
Demosaicing is similar to nailing the angles determined to create the perfect rosette pattern in halftone dots on four color commercial press. Be slightly off in angle and the entire image's color cast shifts ever so slightly. I've seen it on press when I use to do color separations by hand for screenprint output. Screen printing 4 color process would really get screwed if the screen mesh fineness created a mosaiced pattern with t-shirt fabric pattern.
That's why I really respect demosaicing algorithm processes involved with the fine mesh sensor pattern reconstructed on my high rez display. Get it wrong, and you can forget about fixing it with curves and matrices.
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You left out the most influential aspect of your workflow and that being demosiaicing algrorithms which if you don't line 'em up right with your curves and matrices can skew the overall "petina" of the image making it look kinda' funky but in a way you can't put your finger on it.
I don't think demosaicing has that effect, and I have never seen it. In RawTherapee you can select 9 different demosaicers vastly different from each-other and they all produce the same color, *except* if you have an aliasing issue. A plain color woven fabric which provokes aliasing can probably in some circumstances cause different global color result depending on demosaicer. But any color in an area which is not plagued by aliasing will be rendered the same with different demosaicers.
In fact I think the DNG Profile Editor doesn't do demosaicing at all, as you can't zoom to 100% there it doesn't have to, it just takes blocks of 2x2 pixels (so you have all three channels represented) and produce a quarter size image from that which is used for profiling.
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When I recently made printer profile experiments I came to the conclusion that at least 900 patches was sort of required for a high end profile. Can a camera profile be good with only 24 patches is then a question I'd like to investigate together with many more.
I'ld have to say the 900 patches method is a step in the right direction. I've come across discussions online where photographers complain that the 24 patch CCchart just isn't enough to account for properly capturing near full saturation objects under various lighting intensities.
But how to go about doing that appears to be easier dealt with on an image by image basis using the HSL panel that come with most Raw converters. That's what I've been having to do.
Lot of photographers like to shoot neon lights at night and think a camera profile will fix the HSL errors that they think is causing the posterization in the hue transitions. I think they're asking too much from a consumer level camera system. Build a profile using a CCchart made of neon lights. Yeah, that's gonna' work I'm sure.
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I don't think demosaicing has that effect, and I have never seen it. In RawTherapee you can select 9 different demosaicers vastly different from each-other and they all produce the same color, *except* if you have an aliasing issue. A plain color woven fabric which provokes aliasing can probably in some circumstances cause different global color result depending on demosaicer. But any color in an area which is not plagued by aliasing will be rendered the same with different demosaicers.
In fact I think the DNG Profile Editor doesn't do demosaicing at all, as you can't zoom to 100% there it doesn't have to, it just takes blocks of 2x2 pixels (so you have all three channels represented) and produce a quarter size image from that which is used for profiling.
I'm referring to the quality of color changes the editing tools have on the preview that is influenced by the static image formed by a demosiac algorithm.
For instance when I zoom in at 400% in CS5 ACR adjusting the color noise sliders and chromatic aberration selector to get rid of purple fringing on a richly golden autumn leaf I notice either the hue shifts slightly to green or is reduced in saturation. Sliding the Color Noise slider back and forth I can see the screen like subpixel pattern shift underneath very similar to what I saw changing the angles of process color halftone dot rosettes.
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Yes I've got the sense that a standard 24 patch profile often have issues with high saturation colors, and it's easy to explain -- the target does not contain any really high saturation colors. I'm not 100% sure that it actually is the case though, I've not yet made a controlled test.
That it doesn't work for artificial lights at night is a different subject I think as that is typically narrow band sources and often mixed light, I don't think that problem can be solved at all. What you can do with camera profile is to render "accurate" color in a typical daylight color temperature range.
To narrow down the problem area one can look first at the reproduction case, ie fixed light condition (say D50), render as accurate colors as possible in that condition. When the best methods for that has been laid down one can further look into how those profiles behave in extreme light conditions.
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Yes I've got the sense that a standard 24 patch profile often have issues with high saturation colors, and it's easy to explain -- the target does not contain any really high saturation colors. I'm not 100% sure that it actually is the case though, I've not yet made a controlled test.
Which is why any armchair color scientists here should provide colorimetric evidence that 24 patches from the MacBeth is problematic to Thomas Knoll and Eric Chan at Adobe and James Vogh at X-rite who I know would find this valuable. I worked with X-rite while they developed a number of targets for camera profiling and I'm certain such actual evidence would be something those companies would love to see proven.
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I'm referring to the quality of color changes the editing tools have on the preview that is influenced by the static image formed by a demosiac algorithm.
Ah okay, I misunderstood. Good points, noise reduction and defringing etc can certainly have an effect on color. I think it's outside the scope of a profile to correct for that though.
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Which is why any armchair color scientists here should provide colorimetric evidence that 24 patches from the MacBeth is problematic to Thomas Knoll and Eric Chan at Adobe and James Vogh at X-rite who I know would find this valuable. I worked with X-rite while they developed a number of targets for camera profiling and I'm certain such actual evidence would be something those companies would love to see proven.
Me too.
I didn't know you were an armchair color scientist, Andrew?
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I didn't know you were an armchair color scientist, Andrew?
I'm not in real life or on TV. If you can find any post I've ever made, anywhere on the net that I claim to be, you win a big prize.
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Ah okay, I misunderstood. Good points, noise reduction and defringing etc can certainly have an effect on color. I think it's outside the scope of a profile to correct for that though.
Everything about profiling is unfolding on the front end at the source as the sensor response is measured and "dealt" with on the final back end according to some color standard model reference.
But no one knows what the results will be when you start editing a wide range of images that are formed by this front to back standard process viewed and judged on a display. Golden autumn leaf my be slightly on the green side but how would one find in this complex process the cause of it when all the other colors look fine or correct.
Good luck to you investigating this. You've got your work cut out for ya' for sure. It's mind boggling how well all of this works as it does.
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Which is why any armchair color scientists here should provide colorimetric evidence that 24 patches from the MacBeth is problematic to Thomas Knoll and Eric Chan at Adobe and James Vogh at X-rite who I know would find this valuable. I worked with X-rite while they developed a number of targets for camera profiling and I'm certain such actual evidence would be something those companies would love to see proven.
As far as I understand Adobe doesn't use the Adobe DNG Profile Editor for their own in-house profiles. I've heard that they use monochromator and custom software, but I'd love to know more details about it. The bundled color rendition with raw converters has become a competing factor though, so I'd guess it's a little bit of a secret how they do it, just like for Phase One and in the medium format industry as a whole whose color rendition in their own raw converters is a major selling point.
I'll try to devise an experiment to prove that the 24 patches is problematic, or even better prove that it is not so we all can relax :). I've not yet figured out how to do it though, any suggestions are welcome of course. If there is a problem it can be hard to differ between if the problem is too few patches, or the problem is that the color checker is not on spec.
Clearly some think that you can do better than those classic 24 patches (it was designed in the 70's) as there are other manufacturers with other targets with more patches and/or more saturated patches, but maybe they're just trying to sell on the usual "more is better" without actually being better in practice. I don't know (yet).
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Clearly some think that you can do better than those classic 24 patches (it was designed in the 70's) as there are other manufacturers with other targets with more patches and/or more saturated patches, but maybe they're just trying to sell on the usual "more is better" without actually being better in practice.
Agreed, clearly they do. And as yet, no evidence to supply to either company and hence my suggestion.
Clearly if someone's goal is to sell us a target, it's in their best interest to convince us more/different patches are better. I'm pretty sure nothing would make X-rite happier than to sell people another target.
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Another comment regarding the available profile editors.
When it comes to subjective tuning Adobe's own doesn't allow "hue/saturation twists", ie lightness-dependent adjustments. For example it's common that a subjective profile warm up lighter reds and cool down darker reds. I think increasing saturation in shadows is also common. Adobe's own bundled profiles have plenty of this type of hue twists, but the tool they distribute (Adobe DNG Profile Editor) don't allow that type of edits unfortunately.
I looked at QPCard documentation, and it while it supports edits it too seems to be limited to 2D adjustments.
I don't know about the X-rite software.
In all it seems like currently available software is very limited in terms of subjective edits. How to increase or decrease color separation in a certain color range? Cool down shadows, warm up highlights etc.
I do like the concept more of having a neutral twist-free profile and then use the raw converter tools to do the subjective color edits, however most raw converters are designed such that making the really subtle adjustments like done in profiles is not possible to do with the raw converter color tools, and even if you can it sort of clutters the interface when you're doing further edits, so I do see a point of having some subjective adjustments in the profile too.
It seems like currently the possibility to do advanced subjective edits is only available to manufacturers using their own custom in-house software, unless I've missed some software (or feature in a software).
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It seems like currently the possibility to do advanced subjective edits is only available to manufacturers using their own custom in-house software, unless I've missed some software (or feature in a software).
The question I'd have is this: can you apply these edits using tools above the camera calibration pane (using Adobe converter as our example)?
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Okay, google finally helped me find what I've thought would exist out there -- a commercial system for measuring the CFA of the camera.
The german company Image Engineering http://www.image-engineering.de has a product called camSpecs (hardware and software bundled) where you can measure the CFA. It's been discussed briefly in this forum before. It's quite smart, instead of using a monochromator and having to shoot like 80 pictures in 5nm bands they have a standard slide projector with filter narrow band filter slides so you sample several bands per picture. They have a never LED-based "active test chart" in the "camSpecs express" product.
However it's very limited in terms of profile creation, it's more of a system for making DxOMark type of measurements. The only thing you can make in terms of profile is to create a basic color matrix, no LUT stuff, and no ICC or DNG profile creation. So it's still not a complete profiling system.
The price? €9750, plus €2800 for the calibration device, plus VAT. A bit steep considering you'd still have to write your own profile making software :)
Their reference page contains companies like Canon, Nikon, Adobe, Fujifilm, Foveon etc, so I imagine that some of these systems are used by some of these companies when making profiles, but not without additional software...
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As are the ICC apparently:
Using ICC profiles with digital camera images
http://www.color.org/whitepapers.xalter
ICC (organization) can say whatever they want - the reality is different... I guess you do not dispute that rawdigger + argyll based example was provided to you before, no ?
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The question I'd have is this: can you apply these edits using tools above the camera calibration pane (using Adobe converter as our example)?
Lightroom has some crude camera calibration adjustments, and then it has a color tool where can make various adjustments by selecting hue, but you can't select "dark red" and make a hue adjustment and then select "light red" and make a different hue adjustment (or lightness/saturation).
With RGB curves you can make some of these effects but it's more difficult to work with.
The best and most flexible color edit tools in a raw converter I've come across is what's found in Capture One, with it's color editor you can make advanced selections. But I think there are still a few edits that is done in bundled color profiles you can't do in that color editor.
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Camera profile is a whole different animal than a printer profile. You need virtually infinite number of patches to make a camera profile, but so or so profile optimisation for some of these patches will distort the effect in case of other patches.
In the end of the day you'll came up to conclusion, that you can make quite a decent profile with a small number of patches, or can make a better profile optimised for specific patches, or you can play with as many patches as possible in an endless pursuit for the best compromise.
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The original way of applying an ICC profile was to convert to TIFF from the raw converter (using the raw converter's default color) and then handle color management outside the raw converter entirely. This is where the bad reputation of ICC profiles comes from.
digitaldog intentionally writes FUD ;) he is very well aware about the fact that icc profiles can be done from data not subjected to any color transforms
The DNG profile format is a lot easier to understand though, has floating point natively supported, and has more flexibility with dual illuminants and a pre-exposure and post-exposure LUT.
as noted ICC container can have many color transforms stored (multiple LUTs for example), so it is up to the raw converter to use that data (even ICC /organization/ does not approve) pre and/or port exposure...
Writing an ICC to DNG Profile converter software is indeed possible and I'm thinking about doing that, but what you will have to do then is to specify which raw converter the ICC profile was made for
no, you just can write ICC to DCP converter assuming that ICC will be done with for example rawdigger + argyll with the specific purpose of being fed to your converter afterwards - so you have control on how ICC was created and the work is less complex... and you get argyll's ability to work with any target or multiple targets or whatever... now if you want specifically use for example P1 profiles from C1 then I am not sure about legality ...
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Which is why any armchair color scientists here should provide colorimetric evidence that 24 patches from the MacBeth is problematic to Thomas Knoll and Eric Chan at Adobe and James Vogh at X-rite who I know would find this valuable.
Adobe does not use this target to create their own profiles shipped with ACR/LR :) ... wonder why ?
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Agreed, clearly they do. And as yet, no evidence to supply to either company and hence my suggestion.
Clearly if someone's goal is to sell us a target, it's in their best interest to convince us more/different patches are better. I'm pretty sure nothing would make X-rite happier than to sell people another target.
they are pretty much happy with the price vs market with xrite passport... specifically that 99% of their buyers do things like fill the frame with the said target and create profiles for a daylight...
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no, you just can write ICC to DCP converter assuming that ICC will be done with for example rawdigger + argyll with the specific purpose of being fed to your converter afterwards - so you have control on how ICC was created and the work is less complex... and you get argyll's ability to work with any target or multiple targets or whatever... now if you want specifically use for example P1 profiles from C1 then I am not sure about legality ...
I was thinking about creating ICC profiles in a P1 workflow which means you get a P1 type of profile, not "steal" the bundled profiles to get the same look in lightroom, but well I guess that would be a side-effect, but it would certainly not be illegal to provide the tool. Great idea about using rawdigger+argyll though if that's possible...
However concerning software projects, the most interesting I've found so far is to buy a $1200 monochromator (or a $500 off ebay), to measure the CFA curves, and then make profiles based on that. As far as I can see that is the state of the art way to make reference profiles (which you then have some additional tool to make subjective tunings on). It's however not available to consumers as there is no software. To make software that makes something previously only available to manufacturers available to ordinary photo hackers would be super-cool... maybe I would find out that the monochromator/CFA method would be no more effective than a greg macbeth 24 patch color checker though, and then I would cry a bit ;)
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maybe I would find out that the monochromator/CFA method would be no more effective than a greg macbeth 24 patch color checker though, and then I would cry a bit ;)
Exactly. I believe that monochromator saves time in a case of guys like Adobe color engineers, who need to find the best compromise for various objects SPD curves and lighting conditions.
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ICC (organization) can say whatever they want - the reality is different... I guess you do not dispute that rawdigger + argyll based example was provided to you before, no ?
digitaldog intentionally writes FUD
you are totally clueless...
You haven't been around these parts long or written many posts. But just the one's today have convinced me that you deserve your very own spam filter so that whatever comes my way from LuLa from you goes where it belongs.
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Lightroom has some crude camera calibration adjustments, and then it has a color tool where can make various adjustments by selecting hue, but you can't select "dark red" and make a hue adjustment and then select "light red" and make a different hue adjustment (or lightness/saturation).
Those are largely hurt me buttons for most users. If a fixed slider gets the job done, I'm fine with that.
With RGB curves you can make some of these effects but it's more difficult to work with.
If the task can be achieved as I believe you are referring to (subjective editing) I'd suggest that or other rendering tools are both more appropriate and easier for users than building then editing a DNG camera profile.
The best and most flexible color edit tools in a raw converter I've come across is what's found in Capture One, with it's color editor you can make advanced selections. But I think there are still a few edits that is done in bundled color profiles you can't do in that color editor.
Fair enough, perhaps C1 and Adobe need to better provide selective color editing tools to do so. But I hear what you're saying, I still wish for the kinds of tools I had back with LinoColor that offered very powerful selective color editing tools. Point is, baking those kinds of edits into a profile (DNG or ICC) seems difficult for the end user and at the wrong place in a raw converter. But if people what to use a scientific calculator to figure 15% of the restaurant tip, go for it. ;D
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I've some limited experience with DNG camera profiles. All the custom profiles I have made in the DNGPE are better than the results I get from QPcard and X-rite's Colorchecker Passport software. The latter two tweak the matrices, by 'guessing' at the camera's response from the photographed color target. However, the LUT adjustments that these profiles make usually robs the profile of some smoothness. One can see rough transitions in blurry out of focus areas for example.
On some of the ways processing engines affect color, I've also noticed that for LR/ACR PV2010 thinks more colors are blown than they actually are (confirmed by checking in rawdigger), while PV2012 applies aggressive highlight recovery by default, and it is extremely hard to move the sliders around to a point where no highlight recovery is applied. Regardless, I see that PV2012 tends to maintain better looking color in the brightest highlights. Warm daylight colors in PV2010 that are clipped or close to clipping tend to be shifted in hue towards green, while PV2012 maintains a more pleasing color. This is true regardless of the camera profile, Adobe Standard (with hue twists) or my custom daylight DNGPE profile. To observe this phenomenon, zero all the sliders in PV2010, save a copy, then convert to PV2012 and save another copy to compare. So no user additional edits can be blamed for contributing to this shift in color.
I believe I read Iliah Borg on the colorsync list commenting about how camera profiles should be a simple matrix profile, built from monochromator data, with no LUTs involved. That is how Adobe does it to derive their color transform matrices.
Here is a link to a presentation by Wayne Bretl (https://www.dropbox.com/s/yngiz6vc1c7mxn9/Wayne_Bretl_Theoretical_and_Practical_Limits_to_Wide_Color_Gamut.ppsx?dl=0), where he discusses some of the trade offs in mapping color from camera sensors. I think it offers some insight on how to derive the color matrices and the tradeoffs, which you might be interested in.
This is a very intriguing thread. Thank you for starting it Torger, I sincerely hope you figure this out! I tried to about a year ago and couldn't crack it.
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Great post Samuel, and great link. Will look at that presentation in detail (haven't had time yet), it seems to answer lots of questions I have.
The efficiency of pure matrix profiles are indeed an interesting subject. Maybe with "perfect" XYZ coordinates of the RGB primaries color can be very accurate, although the quick look at the presentation seems to suggest that is not the case. One thing is for sure that a camera is more linear than both printers and screens, as linear as it gets, but the color filter responses are not ideal for color matching.
How accurately will a greg macbeth 24 patch profile place the RGB primaries compared to a CFA method is one question. I noted that the camSpecs product had three methods to calculate the RGB primaries from the CFA response, if we're lucky those methods are documented in the literature somewhere so one can test, seems to be a few leads in the presentation. I don't need to get a monochromator for experiments as there's public Nikon D5100 data available for example, and imaging resource has shots of both the 24 patch colorchecker and the larger SG.
You can make basic subjective adjustments with a matrix profile too, like increasing saturation and I *think* Adobe typically does that, ie their matrices are not designed for maximum accuracy but to provide a good basis for that saturated "Adobe Standard" look.
Pure matrix profiles are often favored by "photo hackers" as they have perfect smoothness and perfect linearity (great for HDR merging for example), but if they can actually make reasonable accurate colors I don't know. I've got the sense that they're often quite off, but that may be due to the design method, ie for placement of RGB primaries due to test target limitations, or a subjective placement from a vendor to produce a "look". Possibly the only reason to use a LUT is to make subjective adjustments, but I do doubt it, my current guess is that even with a "perfect" matrix profile you would get improvements in accuracy by adding LUT adjustments.
Another frustrating thing in terms of the lack of profiling software is that there are no good profile evaluation tools, for example to make smoothness vs accuracy tradeoffs in a LUT profile, you have to test with real images and hope that you see, or use a tool like DcpTool and try to visualize how the listed hue/saturation adjustments will affect smoothness.
I think the lack of profiling software and general profiling experience among photographers have created a mythology around camera color. Many think the color is more strongly bound to the hardware than it actually is, and it can be the reason why some pay 4 times the price for an IQ250 rather than a 645z which has the same sensor, just because Capture One IQ250 profile color is subjectively better. I'm convinced that the CCD vs CMOS often debated in MFD forum is more about profiling than hardware differences. If there was proper tools for profile editing and available knowledge how to make great subjective profiles photographers could take some power back from the vendors...
It seems like camera profiling is the least developed aspect of photography color management.
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Looking a bit more at the presentation it seems like a pure matrix profile is not the "ultimate" answer concerning accuracy and gamut coverage. A LUT is required. It should be possible to create that LUT from the CFA responses.
With a matrix profile you miss out on some colors, and create some false out-of-gamut colors. I have before noted that matrix profiles can make colors even outside ProPhotoRGB, but those colors are not real colors...
Also worth noting that there are no "correct" positions of the RGB primaries in the matrix profile, but there's tradeoffs to make between say gamut coverage and chroma noise. Additionally there's also an accuracy tradeoff, a matrix can be optimized to match some colors better than others, which suggests that a matrix derived from a test target with "important colors" may be better than a purely analytical method.
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It seems like camera profiling is the least developed aspect of photography color management.
For a good reason.
Standard CMF used in color management is a very simple model of specific human perception condition. It works well in a stable, controlled environment, and characterises the way how we perceive small color stimulants under D50 lighting.
There's no chance it could work flawlessly in case of digital camera that captures colors in a completely different way than a human eye, and - to make things even worse - in various lighting conditions. No matter what method you'll use, it will eventually fail for some colors, or in some lighting conditions. All you can do is to find the best compromise, but there's no magical method to get significantly "better results" with some more sophisticated tools or magical camera profiling method (as long as it's based on standard CIE XYZ colorimetry).
What we would need to achieve better results is a science-fiction camera and next generation RAW converter, not better camera profiling tools.
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For a good reason.
I don't think so. As discussed in this thread there's more to camera profiling than making accurate colors. There's the subjective tuning of profiles too, and those aspects are really limited in current software. Vendors have their own inhouse tools to make profiles, because no software on the market is flexible enough.
Reproducing skin tones "just right" for your studio portraits is a more about art than accuracy, but to perform this art you need tools and knowledge how to tune this. All this is missing in the tools I've found so far.
It is however a good situation that photographers can't make profiles with "vendor look" if you're Phase One for example. One of the main selling points of Capture One is that color in Adobe Lightroom is (subjectively) much worse even for the same cameras, and there are no good tools for the photographer at hand to design their own look that they like. Capture One supports the IQ250, but not the massively cheaper 645z both with the same sensor. A major selling point is that IQ250 color is subjectively better, and that's (almost) only about the profile. Few photographers understand it though, as camera profiling is not a well-known subject.
If there's something to gain from making the base profile using measured CFA responses like the vendors do instead of using reflective targets is less certain I guess (especially if we're satisfied with Pointer's gamut), maybe it's more about efficiency than quality. Once you've measured the CFAs you can use any type of design method to make your profile without having to pull out the camera again (oh well, you'll still have to do your subjective adjustments on real shots). I guess the only way to find out is to test, or ask someone that is experienced with both methods.
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I don't think so. As discussed in this thread there's more to camera profiling than making accurate colors. There's the subjective tuning of profiles too, and those aspects are really limited in current software.
I strongly agree with Czornyj and further, those tools you desire should be placed outside an ICC profile or DNG profile. Not their job. As for 'accurate' color, major rabbit hole like many aspects of this discussion.
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I agree with Czornyj and further, those tools you desire should be placed outside an ICC profile or DNG profile. Not their job. As for 'accurate' color, major rabbit hole like many aspects of this discussion.
Well, I agree, but the raw converter vendors don't, and actually I think most users actually prefer to have a base look delivered by the profile. Subjective look is currently very much controlled by the profile in the major raw converters, and the tools inside the raw developer typically don't allow for the type of fine-tunings done in a profile.
On the second point you can always run the argument that since absolute accuracy is not possible (as we all know) you can reduce test target gamut coverage further, and dumb down the profiling process even more. Maybe it's true that 24 patch greg macbeth is already way past the limit of diminishing returns, but I'd like to find some better documentation on that than I've found so far, or make my own experiments that can reach to that conclusion.
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Subjective look is currently very much controlled by the profile in the major raw converters, and the tools inside the raw developer typically don't allow for the type of fine-tunings done in a profile.
Can be yes! Doesn’t have to be, wasn't designed to be, rather difficult to achieve compared to editing tools in a raw converter. Do we need better selective color rendering tools? Sure. Is a profile the place to do this? I and others think not.
On the second point you can always run the argument that since absolute accuracy is not possible (as we all know) you can reduce test target gamut coverage further, and dumb down the profiling process even more. Maybe it's true that 24 patch greg macbeth is already way past the limit of diminishing returns, but I'd like to find some better documentation on that than I've found so far, or make my own experiments that can reach to that conclusion.
There lies a huge issue; the gamut of the target itself and the fact our camera systems don't really have a color gamut. And the illuminant and conditions we shoot that target. And how it's processed. As was mentioned here already, treating a camera system like a display or printer in terms of targets, measurements and other processes is fraught with issues. Been that way since way back in the ColorBlind days of ICC color management, hasn't changed much since.
IF the problem is rendering the raw image as you or I desire, we need better rendering tools in the converter. And it's possible we could get them.
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maybe I would find out that the monochromator/CFA method would be no more effective than a greg macbeth 24 patch color checker though, and then I would cry a bit ;)
there mere fact that OEM profiles are not done off 24 patches says that you have a chance to do better - may be you can create your own target for example... there was one person (do not remember where I saw his postings @ colorsync list or here) who actively engaged in creating his own targets for camera profiling (you have spectrophotometer, so you can measure patches for argyll)... he was using some paints and color chips and cuts from exisitng targets and so on, as far as I remember... I think his name was Ben Goren... this dude = http://trumpetpower.com/photos/Exposure
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there mere fact that OEM profiles are not done off 24 patches says that you have a chance to do better - may be you can create your own target for example... there was one person (do not remember where I saw his postings @ colorsync list or here) who actively engaged in creating his own targets for camera profiling (you have spectrophotometer, so you can measure patches for argyll)... he was using some paints and color chips and cuts from exisitng targets and so on, as far as I remember... I think his name was Ben Goren... this dude = http://trumpetpower.com/photos/Exposure
Thanks for the reference, I'll have a look, looks like a really nice user article on the net similar to what I'm thinking about doing.
There's also "HueLight" the guy that sells color profiles to the 645z for example (and people buy them because many are not satisfied with Adobe defaults), as far as I know he uses some self-devised custom method to make his profiles, and adds hand-tuning. Subjective fine-tunings will never be a "mainstream" function, it will be for advanced users with a special eye for color. Therefore I think it's unlikely that we'll see corresponding fine-tune functions inside Lightroom for example.
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TL;DR
There is no way to make good profiles with reflection target. And no chance to make profiles that is colorimetric accurate in general because sensors do not correspond Luther-Ives condition. Only "pleasure color reproduction" rule way to make these things right.
I make some profiles that uses sensor's CMF (color matching functions, spectral responses).
ICC (for Capture One):
https://www.sendspace.com/file/f951ee
https://www.sendspace.com/file/tw6uw5
https://www.sendspace.com/file/277362
https://www.sendspace.com/file/8f2gsq
https://www.sendspace.com/file/dsx7wp
https://www.sendspace.com/file/5dxgl1
DCP (LR, ACR etc):
https://www.sendspace.com/file/lpru4k
https://www.sendspace.com/file/420pg5
https://www.sendspace.com/file/p7b1jh
https://www.sendspace.com/file/cdihaj
Enjoy.
PS. Sorry for my bad english. =)
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Thanks Trantor. I'll certainly have a look.
Would you mind sharing a little about which method/software you have use to create these profiles? I'm very curious to hear...
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There's also "HueLight" the guy that sells color profiles to the 645z for example (and people buy them because many are not satisfied with Adobe defaults), as far as I know he uses some self-devised custom method to make his profiles, and adds hand-tuning.
He does, he got once into a shouting match with Eric Chan :D , as far as I remember the postings in some U2U Adobe-hosted forums ... but I do not recall him sharing his methods or anything that you might be interested in... for such things you really can try to engage directly people behind the profiles in actual raw convertes - Chan or BG of Iridient or Borg of RPP or even what was his name... Kuhlmann or Esben Myosotis (???) from PhaseOne ... the skillfully posed polite question goes a long way, while not creating an impression that you are trying to extract something that they consider a trade secret... so you really need to spend time thinking what and how to ask and then you might score a knowledge
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Thanks Trantor.
I recall somebody (3rd party) posted about his profiles @ http://www.rudtp.pp.ru last year... examples were good (or very good)
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method/software you have use to create these profiles?
I make my custom software. Actually all calculations does in Matlab plus sort of handmade works (eg matrix fitting, whitepoints iteration etc).
Schema is: CMF + spectral "paths" (~50K items) + spectra of selected illuminants (A, D50, D65 etc) -> sensor gamuts under selected illuminants -> warping (Shepard's method) sensor gamuts to human gamuts under selected illuminants -> LUT's for every illuminant -> resulting profiles.
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http://www.rudtp.pp.ru
Yeah. Same point. =)
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the starting point for OP this way is - either procure spectral response for a particular camera (sensor + CFA + whatever optics on top) from manufacturer or buy/rent monochromator (or make some friends in a local university/etc with such equipment available) to measure
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Thanks for the reference, I'll have a look, looks like a really nice user article on the net similar to what I'm thinking about doing.
You should contact Eric Walowit and talk to him about his idea of capture specific profiles done on the fly when shooting while measuring the actual capture illuminant. Contact me off list and I'll give you his email. What Eric proposes makes so much more sense than treating a digital camera like a printer in terms of a profile.
https://www.linkedin.com/pub/eric-walowit/4/4a0/793. No armchair's anywhere near this fellow.
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I make my custom software. Actually all calculations does in Matlab plus sort of handmade works (eg matrix fitting, whitepoints iteration etc).
Schema is: CMF + spectral "paths" (~50K items) + spectra of selected illuminants (A, D50, D65 etc) -> sensor gamuts under selected illuminants -> warping (Shepard's method) sensor gamuts to human gamuts under selected illuminants -> LUT's for every illuminant -> resulting profiles.
Thanks! I think I understand.
I've had a look at the profile for Canon 5Dmk2, what differs the "GM" from the "NOGM"?
I've noted that the GM has a LookTable and the NOGM has not, otherwise they are equivalent. The GM version looks slightly more saturated.
I made a quick comparison of the same ~D50 scene using matrix only, Adobe default, Adobe DNG Profile Editor on the color checker in the scene, Trantor's GM and NOGM, plus Capture One's 5Dmk2 generic profile, all rendered in RawTherapee which supports both DNG and Capture One icc.
The scene is not particularly good only a colorchecker on a chair (an old shot from another occasion, I don't have the camera here now so I can't reshoot), used that because I have the chair and light here so I can see it in reality.
Making a casual evaluation of this scene I'd say the matrix profile is quite obviously off, Adobe Standard is not too bad but have some color shifts, easier detected on the subtle colors of the wooden chair than on the colorchecker itself, the DNG PE generated profile is clearly over-saturated and got yellow too orange, Trantor's profiles and Capture One's are all quite similar and looks most correct to my eyes.
Trantor's profile seems to have some issue with the dark blue patch on the color checker, it's a little bit too low saturation, and the bright yellow is too orange. Overall Capture One's profile is the most correct to my eyes.
As the light is a florescent print viewing light it's not as good as true D50 though. I was surprised that DNG PE did not make a better result which actually got the specific color checker in the scene under the specific light to work with, but it could make all sorts of tradeoffs against accuracy.
I then tested the same five profiles side by on a couple of landscape scenes with sunset type of light. I don't have the color memory to know which one that looks most realistic, but the same type of differences as on the colorchecker scene could be noted, quite large differences between matrix-only, adobe standard, DNG PE which all had their own unique looks, and then quite small (but detectable) differences between Trantor's two and Capture One's.
It seems to me from this brief test that Trantor's method works well, but maybe can be improved upon, and that DNG PE is not really that good, but it can be the software's fault rather than the color checker.
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what differs the "GM" from the "NOGM"?
Profiles marked with "GM" contains gamut mapping LUT that maps ProPhoto gamut into sRGB gamut. Marked with "NOGM" do not have gamut mapping table respectively.
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Profiles marked with "GM" contains gamut mapping LUT that maps ProPhoto gamut into sRGB gamut. Marked with "NOGM" do not have gamut mapping table respectively.
Ah... why would one want to map from Prophoto to sRGB? As DNG's color space is defined as Prophoto the raw converter should take care of gamut mapping, right?
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raw converter should take care of gamut mapping, right?
I don't like how it works in LR, Photoshop etc in some cases. Example in attachment. LR relative gamut mapping vs my gamut mapping.
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So you've figured out a way to track luminance and mate it to hue/sat and preserve that relationship with linear increase in luminance or overall brightness. Those are really good results.
I've had to resort to creating huge shepherd hook shaped point curves and HSL adjusts in ACR/LR combined with a DNG profile to get those results, so you're saying you can now do it all in a profile?
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so you're saying you can now do it all in a profile?
Yeah, thats right. Algorithm is pretty smpile in Lch (lightness/chroma/hue) space:
L = const, h = const
c_in -> source gamut by chroma
c_out -> destination gamut by chroma
c_in_max - > source gamut by chroma maximum
c_out_max -> destination gamut by chroma maximum
[0 < c_in < c_in_max]
[0 < c_out < c_out_max]
if c_in_max > c_out_max
{c_result = sigmoidal compression function(c_in, c_out) }
else { c_result = c_in }
Compression function looks like this:
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Some nice complex work I could never rap my head around, but I'm glad there's someone who can.
Can you track this compression and trace it/or keep it tied to measurements of the actual scene or are you going about measuring how the sensor responds to the scene.
How does that profile make normal gamut scenes with less saturated objects appear? Less saturated overall?
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In my case this is static compression/mapping from ProPhoto to sRGB. For DCP-profiles I use two first LUT's for correction (by warping) sensor gamut to the human gamut and second LUT for gamut mapping (ProPhoto -> sRGB). LR and other RAW-processors do not use spatial gamut mapping that depends on scene gamut.
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Can you post another image with not so saturated color using the same profile you applied to the rose? I'm trying to see if the profile renders a wide range of scenes with a consistent balance.
Lack of color balance is the main issue current profiles have a hard time with across a wide range of scenes depending on the level of saturation of objects and illuminant in the scene. A lot of this lack of balance can be exacerbated by the quality of UV/IR filtering on the sensor which can be different between camera brands & models.
In my experience with my own camera I never know when these saturated objects are going to go off the charts while others don't. I don't know if it's possible a profile can fix that. Yours might.
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Worth noting is that if you print the gamut mapping can be controlled by the ICC profile, via the perceptual intent. However I typically reduce gamut in the raw converter to fit the printer's gamut and then print relative colorimetric with black point compensation, and then all gamut mapping will take place in the raw converter.
Tools to reduce gamut in a raw converter manually is just things like decreasing overall saturation, reduce saturation (or value) for specific problematic colors etc.
There is no native support in DNG Profile to make gamut mapping, but of course you can do it in Trantor's way, it means that you should only use the gamut mapping version if you have issues with out of gamut colors.
Personally I don't think gamut mapping is a big issue, for my own work I'm satisfied with doing manual adjustments of problem colors. I generally don't have very saturated colors in my pictures though. sRGB does not cover Pointer's gamut so there can be issues with flowers etc, AdobeRGB covers most of it but still not all.
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I believe I read Iliah Borg on the colorsync list commenting about how camera profiles should be a simple matrix profile, built from monochromator data, with no LUTs involved. That is how Adobe does it to derive their color transform matrices.
I though they used a target based system? I might be wrong.
iain
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From visual observation gamut mapping requires luminance to be factored in with the luminance of the display which also has gamut limits. Luminance seems to be the black hole for defining exactly how it should be rendered on a ICC calibrated/profiled display.
It's trying to figure out if the failure to preserve HSL relationships that crush flower detail as in the rose example happens at the capture stage or processing stage with software and how it maps it to the luminance of the display.
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Can you post another image with not so saturated color using the same profile you applied to the rose?
Yeah. Sure.
GM:
(http://ib4.keep4u.ru/s/2015/03/10/19/19a62a6095e71693edcb41d13518d9aa.jpg) (http://keep4u.ru/full/19a62a6095e71693edcb41d13518d9aa.html)
NOGM:
(http://ib4.keep4u.ru/s/2015/03/10/b8/b81fde938091a990b09e5a4744466fd5.jpg) (http://keep4u.ru/full/b81fde938091a990b09e5a4744466fd5.html)
GM:
(http://ib4.keep4u.ru/s/2015/03/10/20/206674990d9d8bfbb855e85143e7c3cd.jpg) (http://keep4u.ru/full/206674990d9d8bfbb855e85143e7c3cd.html)
NOGM:
(http://ib4.keep4u.ru/s/2015/03/10/88/88d3ee2435b7e0cb142f88e765a101c7.jpg) (http://keep4u.ru/full/88d3ee2435b7e0cb142f88e765a101c7.html)
GM:
(http://ib4.keep4u.ru/s/2015/03/10/ce/cec08e0dbe5f502187c10eca00cae65f.jpg) (http://keep4u.ru/full/cec08e0dbe5f502187c10eca00cae65f.html)
NOGM:
(http://ib4.keep4u.ru/s/2015/03/10/b3/b3ce81da2a55063173e6b4de673b0f0a.jpg) (http://keep4u.ru/full/b3ce81da2a55063173e6b4de673b0f0a.html)
GM:
(http://ib4.keep4u.ru/s/2015/03/10/b7/b76c4e1a81f2f706ec7b5fc836828ceb.jpg) (http://keep4u.ru/full/b76c4e1a81f2f706ec7b5fc836828ceb.html)
NOGM:
(http://ib4.keep4u.ru/s/2015/03/10/49/4913e9b8fc2845bbe1c61032ed78897e.jpg) (http://keep4u.ru/full/4913e9b8fc2845bbe1c61032ed78897e.html)
GM:
(http://ib4.keep4u.ru/s/2015/03/10/d4/d406a95e902fe854cfd8cdd6a0ca722a.jpg) (http://keep4u.ru/full/d406a95e902fe854cfd8cdd6a0ca722a.html)
NOGM:
(http://ib4.keep4u.ru/s/2015/03/10/39/3968560a230204d55b1593d7033db3d1.jpg) (http://keep4u.ru/full/3968560a230204d55b1593d7033db3d1.html)
All pictures by Canon 6D.
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Thanks, Trantor.
I can barely tell the NOGM from the GM which I'm guessing is as it should seeing that the differences look similar to assigning an sRGB-ish gamut monitor profile to sRGB encoded image. Their gamuts are so close that there are only subtle differences.
I had to download the CCchart examples and layer one on top of the other in Photoshop turning the top layer off/on to see the subtle changes.
The rose's scene gamut must be beyond the Canon 6D's gamut capture capability by a considerable degree compared to the 5 you've posted.
Very informative demonstration, Trantor. That's some really good work figuring all that out.
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It's not beyond 6D'2 gamut - it's compressed from 6D's gamut (rendered to ProPhoto) to sRGB. RelCol rendering intent in LR et al. flattens all OOG colors to the most saturated, colormetric consistent colors available in sRGB.
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It's not beyond 6D'2 gamut - it's compressed from 6D's gamut (rendered to ProPhoto) to sRGB. RelCol rendering intent in LR et al. flattens all OOG colors to the most saturated, colormetric consistent colors available in sRGB.
This word "compression" as it is used in these discussions appears to not render the same across a wide range of apps that apply it to the data with regard to rendering definition and detail as in Trantor's rose example vs how it's rendered like say in ACR/LR.
Now whether this detail and definition that is revealed through compression can be attributed to gamut mapping still doesn't indicate that detail was within or outside any gamut description model or construct unless the rose detail was actually measured with a spectro. This could just be on account of the limits of the slider tools within each software that are suppose to bring out this detail. I saw this kind of blown detail recovered with a severe shepherd's hook curve edit in cloud highlights on jpegs derived from minilab scan years back but I could never say that was on account of any gamut mapping.
Anyone can assign LMS cone response numbers, XYZ, HSL, HSV etc., pick any color description model of your choice but to attribute it to the gamut capture of the device and prove it are two different things. All I'm trying to do is understand and locate where this loss of detail comes from on a wide range of cameras that some lab outfit I've never heard of now says all have a particular 3D gamut shape and size.
No one is explaining the differences seen in previews between apps by applying their own version of "compression" to bring out detail.
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It's not unlikely that the red rose had saturated enough colors to be outside the sRGB gamut, but probably not by much. The image below left shows a comparison between Pointer's gamut (gamut of all possible reflected colors, the irregular shape), and sRGB (the triangle). Red can come outside but not that much. The right shows a comparison with the huuuge Prophoto.
(http://www.tftcentral.co.uk/images/pointers_gamut/figure8_sRGB%20and%20pointer%20CIE1931.jpg) (http://www.tftcentral.co.uk/images/pointers_gamut/figure18_ProPhoto%20RGB%20and%20pointer%20CIE1931.jpg)
(sorry image links seem to break, but you can look at the article at TFT central: http://www.tftcentral.co.uk/articles/pointers_gamut.htm)
Trantor's gamut mapping is a static mapping though as it's in the profile, ie it doesn't know how little it needs to compress, it compresses from the much larger prophoto space and will thus lower saturation more than needed. It would be interesting with a gamut mapping from Pointer's gamut to sRGB, it would compress considerably less and it would handle all reflected colors (in theory at least).
Anyway, as far as I understand Trantor's profiles are designed for accuracy as good as possible, ie no intentional saturation increase. How accurate Trantor's 6D profile actually captures the saturated red tones in that light condition is hard to know of course. Of all things I've read so far I think it's quite safe to say that a modern digital camera with a profile made for the purpose can capture fairly accurate colors a far bit outside sRGB.
I'm not sure this is true, but I suspect that a virtually generated profile from measured camera response (like Trantor's profile) can be more exact for saturated colors than a profile made the traditional shoot-a-colorchecker-way, but probably a colorchecker can achieve better accuracy for colors close to its actual patches.
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Trantor's gamut mapping is a static mapping though as it's in the profile, ie it doesn't know how little it needs to compress, it compresses from the much larger prophoto space and will thus lower saturation more than needed. It would be interesting with a gamut mapping from Pointer's gamut to sRGB, it would compress considerably less and it would handle all reflected colors (in theory at least).
Hi Anders,
I agree, although Trantor's compression is non-linear as I understand it. Bruce Lindbloom already took a similar approach by designing his Beta RGB (http://www.brucelindbloom.com/BetaRGB.html) colorspace, which takes into account the three dimensional gamut hull of many important colors that needed to be accurately encoded, yet with maximum efficiency for creating as small a gamut hull as possible (to minimize the quantization step size of the integer number encoding precision). I'm not sure about Pointer's gamut in 3D, how well it covers very dark and very bright colors.
Cheers,
Bart
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Color balance is the best that we can achieve over exact accuracy which it appears from Trantor's examples requires various levels of compression depending on the scene gamut to achieve consistency across a wide range of scene gamuts. I would have to say though that Trantor's examples overall are not accurate to what those scenes should look like given the light characteristcs which appears beefs up contrast which can have a major influence not only in the rendering of saturated colors but also viewer perception.
As a side note I conducted an experiment today by photographing my calibrated 6500K, 100cd/m2, 2.2gamma, sRGB-ish display showing an image of my own CCchart whose Lab numbers for each patch are exact including the gray patches read in Photoshop. I built a single illuminant profile using the most current DNG PE Wizard and the resulting profile didn't make much of a difference between the normally produced profile. Blue skies in landscapes were slightly magenta and brighter and greens were a bit cool. Cyan's didn't change at all understandably since it's an sRGB display.
The neat thing about doing it this way is that the actual CCchart patches could be edited to achieve a result with other colored (wider gamut) test objects in the scene (instead of editing the Table & Calibration panel through DNG PE which tends to create artifacts if you go too far). Those with AdobeRGB gamut displays would have wider range of colors such as cyan's to tweak and bring out applying the profile to scenes that have these hues. It will also give some indication of the gamut capture capability of the camera.
I have very richly intense cyan objects that my camera can't reproduce. I'm not saying this is the ultimate in achieving accuracy, just a way to creating and editing the results of a DNG profile that doesn't require using the DNG PE editor or any software presets that have to tag along with the custom profile.
It's worth a try and not much of a hassle conducting this experiment but it did give me an idea of what the Wizard actually corrects for if you screw up the colors.
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The efficiency of pure matrix profiles are indeed an interesting subject.
DxO provides a Metamerism Index as part of their sensor measurements and KPIs,
it indicates the degree of compliance with the Luther-Ives condition, so that in the ideal case the "sensor gamut" could be described by one simple matrix profile.
A brief description is given here (http://www.dxomark.com/About/In-depth-measurements/Measurements/Color-sensitivity), however, it is also stated that the value is not particularly meaningful to discriminate DSLR sensors which are typically all in the 75 to 85 range (as opposed to low-end cameras such as camera phones).
Also, it does not allow a direct conclusion if matrix-to-matrix-interpolation would be good enough for "ordinary photographic purposes" (as opposed to reproduction tasks), means to have a reasonably accurate starting point in order to work to a pleasing rendition.
From my experience, this matrix approach has become significantly better over the past 10 years or so and with today’s cameras. In the past there were cameras which could not be reasonably calibrated in ACR by tweaking the matrix primaries with the corresponding sliders. There often was an unconquerable dualism of e.g. getting the red hues right but making the skin hues worse, and vice versa. Later on, the Nikon D5100 which was mentioned somewhere along this thread was my first camera where I concluded that "matrix" (matrix-to-matrix-interpolation) is good enough for me.
However, Adobe went in different direction with the Adobe Standard profiles which replaced the former ACR x.y matrix profiles. Initially there was a LookTable added, however, since 2 or 3 years there is also a HueSatDelta table (actually 2 of it, one per illuminant) which I understand are part of the accuracy compartment of the profile next to the matrices.
Peter
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It will also give some indication of the gamut capture capability of the camera.
Sensor gamut don't have a "gamut capture capability". Only shape of his convex hull. You cannot achieve this convex hull without capture all "border" (high chromaticity) spectra.
For example convex hull of Canon 6D sensor gamut (vs human vision gamut):
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Sensor gamut don't have a "gamut capture capability". Only shape of his convex hull. You cannot achieve this convex hull without capture all "border" (high chromaticity) spectra.
For example convex hull of Canon 6D sensor gamut (vs human vision gamut):
My understanding of how sensors record RGGB filtered photons on a luminance scale per pixel site as defined as voltage readings and converted to 1's & 0's by the A/D converter tells me that there is no way to attest any color gamut 3D model of a sensor until those voltage charges as correlated to 1's & 0's are defined as color after demosaicing in an image processor.
From my understanding you'ld have to measure how many luminance level variations between zero charge to full saturation of each pixel site that determines how many possible levels of intensity of RGGB and compare it against the pixel site right next to it and thus nearest neighbor. It is these levels of variation between pixel sites (excluding noise) that would be the only way to define how many combinations of color that are possible a sensor can record but then to define those combinations requires reconstruction in an image processor on the computer.
How and at what stage are the voltage variants at each pixel site defined by a 3D color gamut model?
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How and at what stage are the voltage variants at each pixel site defined by a 3D color gamut model?
You don't need to demosaic to get RGB responses, as a test patch covers a bunch of pixels so you get plenty for each R G and B. When you've measured RGB filters like Trantor you don't need to shoot test targets, you can feed the camera model with "virtual test patches", including single wave lengths so you can trace the spectral locus for example (if I understand correctly Trantor's plots above is a result of spectral locus tracing). Being able to work with virtual test patches is necessary to have a gamut discussion, as a reflective test target never can cover any extreme colors.
Printer+paper gamuts are simple, the reason is that we can print all colors a printer can reproduce onto a number of papers and accurately measure them, and we get an accurate gamut.
The printer is an output device, so the question is "which colors can it reproduce?", with the camera the question is "which colors it can register?".
With the camera a problem is that we can't make a test chart that covers all colors we can see. If we could the camera's gamut could be defined as covered by all test patches that gives us a unique RGB value. In other words all colors the camera can differ.
With the virtual method we can generate any test patch spectrum, however the variations are infinite and I don't know if there is a good method to generate only the ones we need to appropriately cover all colors the eye can see. Maybe there is, Trantor may know. If there is we could do the above, ie feed the measured camera response curves with all human detectable spectrums and see how many of those that yields a different RGB value. Doing it all inside Matlab or other software we can test millions of virtual patches.
The next step is however that RGB values need to be mapped to *correct* XYZ positions. This is the job of the profile. A matrix-only profile will typically only succeed placing low saturation colors reasonably correct and the high saturation colors will be way off, possibly in out-of-human-gamut positions. A LUT profile can make the best of it, but there may be reasons to not optimise solely for XYZ accuracy as many extreme colors are never seen in a real scene.
When you have a profile that translates only subset of of RGB combinations to correct XYZ coordinates and many get into grossly incorrect positions or even out of human gamut, what is then the gamut of the camera+profile combination? There is no clear definition, and I think one should then rephrase the question to something like how large is the gamut where this camera+profile combination can produce colors with a Delta E smaller than X (where X is quite large, say 10)?
Probably it's wise to optimize a profile to make good color match within say Pointer's gamut and relax matching of extreme colors.
It's also worth noting that a camera may (might?) also be able to separate some spectrums that the eye can't. Using the human eye as reference I guess we should consider those colors invalid and a LUT profile could merge them to the same XYZ coordinate, but from an artistic reason we may want them to be separated anyway.
All these issues is the reason some say "camera's have no gamut". With a printer you just need a high quality ICC profile and a profile viewer and you'll see what colors it can correctly reproduce. Looking at a camera ICC or DNG profile you cannot see what colors it can accurately capture.
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> You don't need to demosaic to get RGB responses, as a test patch covers a bunch of pixels so you get plenty for each R G and B.
by the way - what are the nuances for RG1BG2, where G1 != G2 - a common thing in many cameras (not talking about CYGM or RGBE)... we need to pay attention how that will be done by demosaick that will convert camera's RG1BG2 into camera's RGB, no ?
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It's also worth noting that a camera may (might?) also be able to separate some spectrums that the eye can't.
or how we deal with metameric failures where camera (it's model represented by those measured curves) can't distinguish two colors that we can - so how do we assign them, they might be sufficiently different
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TL;DR
And no chance to make profiles that is colorimetric accurate in general because sensors do not correspond Luther-Ives condition.
So true and yet, that single important fact seem to have been ignored.
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Digital cameras don't have a gamut, but rather a color mixing function. Basically, a color mixing function is a mathematical representation of a measured color as a function of the three standard monochromatic RGB primaries needed to duplicate a monochromatic observed color at its measured wavelength. Cameras don’t have primaries, they have spectral sensitivities, and the difference is important because a camera can capture all sorts of different primaries. Two different primaries may be captured as the same values by a camera, and the same primary may be captured as two different values by a camera (if the spectral power distributions of the primaries are different). A camera has colors it can capture and encode as unique values compared to others, that are imaginary (not visible) to us. There are colors we can see, but the camera can't capture that are imaginary to it. Most of the colors the camera can "see" we can see as well. Yet some cameras can “see colors“ outside the spectral locus however every attempt is usually made to filter those out. Most important is the fact that cameras “see colors“ inside the spectral locus differently than humans. No shipping camera that I know of meets the Luther-Ives condition. This means that cameras exhibit significant observer metamerism with respect to humans. The camera color space differs from a more common working color space in that it does not have a unique one to one transform to and from CIE XYZ. This is because the camera has different color filters than the human eye, and thus "sees" colors differently. Any translation from camera color space to CIE XYZ space is therefore an approximation.
The point is that if you think of camera primaries you can come to many incorrect conclusions because cameras capture spectrally. On the other hand, displays create colors using primaries. Primaries are defined colorimetrically so any color space defined using primaries is colorimetric. Native (raw) camera color spaces are almost never colorimetric, and therefore cannot be defined using primaries. Therefore, the measured pixel values don't even produce a gamut until they're mapped into a particular RGB space. Before then, *all* colors are (by definition) possible.
Raw image data is in some native camera color space, but it is not a colorimetric color space, and has no single “correct” relationship to colorimetry. The same thing could be said about a color film negative. Someone has to make a choice of how to convert values in non-colorimetric color spaces to colorimetric ones. There are better and worse choices, but no single correct conversion (unless the “scene” you are photographing has only three independent colorants, like when we scan film).
Do raw files have a color space? Fundamentally, they do, but we or those handling this data in a converter may not know what that color space is. The image was recorded through a set of camera spectral sensitivities which defines the intrinsic colorimetric characteristics of the image. One simple way to think of this is that the image was recorded through a set of "primaries" and these primaries define the color space of the image.
If we had spectral sensitivities for the camera, that would make the job of mapping to CIE XYZ better and easier, but we'd still have decisions on what to do with the colors the camera encodes, that are imaginary to us.
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I don't know if there is a good method to generate only the ones we need to appropriately cover all colors the eye can see.
I multiply spectral data of Munsell book of color by random numbers in each band. Not brilliant but usual.
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Just for clarification.
Any translation from camera color space to CIE XYZ space is therefore an approximation.
I think that free-form-deformation (FFD) is more useful technique than "clean" approximation. Approximation are worst to predict in some cases.
https://youtu.be/7Pe-RPLMeDI
but no single correct conversion
No single linear conversion.
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or how we deal with metameric failures where camera (it's model represented by those measured curves) can't distinguish two colors that we can - so how do we assign them, they might be sufficiently different
I think that one is easy, if the RGB values are the same then the XYZ output will be the same. You could of course argue that that XYZ coordinate should correspond to the "center" of the local space it can't differentiate rather than just on of the test patches XYZ coordinates, and finding that center will not be easy. I think it's a minor problem, I'd probably not search for any center but just place it based on maximizing smoothness.
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> You don't need to demosaic to get RGB responses, as a test patch covers a bunch of pixels so you get plenty for each R G and B.
by the way - what are the nuances for RG1BG2, where G1 != G2 - a common thing in many cameras (not talking about CYGM or RGBE)... we need to pay attention how that will be done by demosaick that will convert camera's RG1BG2 into camera's RGB, no ?
G1 != G2 is a manufacturing limitation where you have some blue taint in the green filter on one row and red taint on the next. Difference is about 1%, probably monochromator measurement errors will be larger, but anyway we would average over lots of pixels which the demosaicer will also do, ie no meaningful difference.
There will be errors in many places of the profiling process, one challenge is to figure out which errors are large and which are small, which we need to take into account and which we can ignore.
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A profile can skip the matrixing approximation alltogether and jump directly to a LUT solution. Phase One's ICC profiles goes from RGB directly to Lab so they incorporate chromatic adaptation in the profile too.
With DNG profiles you can't skip a matrix but you don't really need them to make a sane result, you can just drag colors into desired position with the LUT.
To get deeper into understanding of the limitations of camera color it's a good start to look at pure linear matrix profiles though.
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So anyone want to answer or take a guess at how many photons each pixel site of a sensor can contain between zero charge to max charge to present a specific but variable charge so the A/D converter can assign a luminance number to define 1's & 0's?
How many variants of charge per pixel translates into a voltage reading that can be assigned a color? 255 levels as in digital language? Millivolts as in million levels of luminance variation?
Torger quote:
When you've measured RGB filters like Trantor you don't need to shoot test targets, you can feed the camera model with "virtual test patches", including single wave lengths so you can trace the spectral locus for example
How can you measure a sensor's RGGB filter? You pull it off the sensor and subject it to transmissive light and record what the CIE Lab numbers indicate off the spectro? What are those Lab numbers with the RGGB filter backlit at full saturation vs half luminance down to just barely visible luminance?
A 2D spectral locus doesn't include luminance variation, the point I keep making about the pixel site voltage variances which as you can see from the rose example missed the mark on luminance interpretation at the pixel site which required a compression curve to correct for. A 3D model will have to be employed to effectively and consistently characterize a sensor's response to real world lit objects subjecting the sensor to near full saturation.
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So anyone want to answer or take a guess at how many photons each pixel site of a sensor can contain between zero charge to max charge to present a specific but variable charge so the A/D converter can assign a luminance number to define 1's & 0's?
How many variants of charge per pixel translates into a voltage reading that can be assigned a color? 255 levels as in digital language? Millivolts as in million levels of luminance variation?
Torger quote:
How can you measure a sensor's RGGB filter? You pull it off the sensor and subject it to transmissive light and record what the CIE Lab numbers indicate off the spectro? What are those Lab numbers with the RGGB filter backlit at full saturation vs half luminance down to just barely visible luminance?
A 2D spectral locus doesn't include luminance variation, the point I keep making about the pixel site voltage variances which as you can see from the rose example missed the mark on luminance interpretation at the pixel site which required a compression curve to correct for. A 3D model will have to be employed to effectively and consistently characterize a sensor's response to real world lit objects subjecting the sensor to near full saturation.
There is a commercial product called "camSpecs" which can be used to measure the filters, but you can also make your own setup using a stable full spectrum lamp (halogen lamp), a monochromator, the camera, and some cloth and duct tape to shade :). With the monochromator you can create a single bandwidth light, so you step through from 380 to 730nm at 5nm intervals for example and shoot one frame for each. Then you use rawdigger manually or preferably write your own custom software to parse the 90 files or so to get a raw value readout for each bandwidth and color averaged over a number of pixels to reduce noise. Then you will get curves, note that you need to scale them for the lamp's spectrum (which you can measure with a spectrometer). Here's one setup described, a bit more complex and automated:
https://spectralestimation.wordpress.com/data/
Due to the linear behavior of the camera's pixels (just linear photon counters) you don't need to vary luminance in the measurement.
Concerning how many photons that are counted per pixel it varies between sensors, it's called "full well capacity". Those that work with astro-photography are often intersted in this number so there are measurements out there. It can be 40000 or so per pixel, larger pixels usually means larger full well capacity. Regarding how many unique steps you can get from it I think DxOmark's "tonal range" measurement is a good indication.
When you have measured the filter response you can then calculate which signal (raw value) the camera will produce for any type of spectrum, that is you can the perform a profiling and generate a profile mathematically, like Trantor has done.
I'm not sure if Trantor has measured the cameras or if he has used any public measurement data. The link above has measurement data for the Nikon D5100 for example so anyone can try to make a profile from that.
There will be some measurement errors when getting the curves of course. I think that for reproduction photography the best method will be the traditional test target method (likely smaller measurement error for the targeted colors), but when making a profile for generic use it can be an advantage to know the camera's behavior also for saturated colors that cannot be reproduced with a test target. The two methods could be combined of course. But as said there are no available software for consumers to do this, vendors have their own custom software, and researchers their own (often Matlab scripts).
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the point I keep making about the pixel site voltage variances which as you can see from the rose example missed the mark on luminance interpretation at the pixel site which required a compression curve to correct for. A 3D model will have to be employed to effectively and consistently characterize a sensor's response to real world lit objects subjecting the sensor to near full saturation.
I think you're mixing up gamut limits of screen and print with recording correct color. Even if the camera+profile is able to record a correct XYZ coordinate it may be outside the screen's gamut and then the color will be clipped or compressed in some way, which happens in the red rose example. That's a separate problem, which Trantor has chosen to solve with a special gamut map profile, but you can also solve it with manual compression be reducing saturation or value of the problematic color. I personally prefer to do it manually, and like the camera+profile to capture as correct colorimetric coordinates as the hardware+LUT profile allows.
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So anyone want to answer or take a guess at how many photons each pixel site of a sensor can contain between zero charge to max charge to present a specific but variable charge so the A/D converter can assign a luminance number to define 1's & 0's?
Tim, it's irrelevant, because us mortals can only access the data that comes out of the ADC and gets written to a Raw file. But if you insist, the sensor well can hold more electrons than the ADC will use. From what I've read, something like 70% of true full well is used by the ADC, because above that level, the sensor response gets to be too non-linear.
How many variants of charge per pixel translates into a voltage reading that can be assigned a color? 255 levels as in digital language? Millivolts as in million levels of luminance variation?
Depends on the camera, and the ISO settings which may influence the ADC gain that is used. A 14-bit ADC can typically output some 16384 levels of intensity per color plane, although some 1024 may be subtracted for read-noise, leaving some 15360 individual levels. At unity gain settings, this will translate to 1 digital number per converted photon, at lower ISO settings that would be e.g. 4 photons per DN at ISO 100, or thereabouts. All this is at the linear gamma Raw level we need for color calculations. Final gamma pre-compensation for the output modality will reduce the remaining integer levels if we do not stay in floating-point number representation.
The reason for you asking escapes me a bit, because we have to deal with what the sensor electronics unveil to us, and there may be other mechanisms involved like WhiteBalance precompensation (typically multiplies the Red and Blue color readouts with a factor before writing to Raw), and/or (lossy) compression, and/or non-linear tone curves. Anyway, the short story is that we could get some 13.9-b/ch precision from a Raw file (after managing photon shot noise, Read noise, Dark current, Pixel Response Non-Uniformity, and pattern noise), in other words some 3.6x10^12 possible coordinate positions, of which only a part are utilized for humanly discernible differences, AKA colors.
Cheers,
Bart
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Tim, it's irrelevant, because us mortals can only access the data that comes out of the ADC and gets written to a Raw file.
you need to change that to only "written to a Raw file", because mortals can't do anything about what firmware does in between... yes, there are people who (can) write firmware for cameras, but then I did not see anyone here.
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you need to change that to only "written to a Raw file", because mortals can't do anything about what firmware does in between... yes, there are people who (can) write firmware for cameras, but then I did not see anyone here.
Hi,
I'm quite sure there are mortals who can intercept the data before it gets written to Raw (e.g. the Magic Lantern crew), but most of us simpler mortals indeed can't... ;).
Cheers,
Bart
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you need to change that to only "written to a Raw file", because mortals can't do anything about what firmware does in between... yes, there are people who (can) write firmware for cameras, but then I did not see anyone here.
Firmware doesn't do much for most cameras in terms of changing ADC readout, but there are exceptions (often followed by loud criticism from users, as users tend to dislike "cooked" raws). In terms of camera profiling we don't need to worry about it though. We can safely look at the camera as a device with linear pixels and we get the data in the raw file. We may need to perform black level subtraction before we can make filter response measurements.
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Hi,
I'm quite sure there are mortals who can intercept the data before it gets written to Raw (e.g. the Magic Lantern crew), but most of us simpler mortals indeed can't... ;).
Cheers,
Bart
true, but then who knows how many layers of firmware Canon cameras have... not being an expert in ML at all I might still suggest that ML is running in an outer layer while Canon still have inner layer, no ? like for example in OS there might be a kernel-level/mode and non kernel level/mode (user space) drivers.
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true, but then who knows how many layers of firmware Canon cameras have... not being an expert in ML at all I might still suggest that ML is running in an outer layer while Canon still have inner layer, no ? like for example in OS there might be a kernel-level/mode and non kernel level/mode (user space) drivers.
It feels like we're drifting away in a tangent here...
The only way this would be relevant in terms of camera profiling is if it would introduce some sort of non-linearity. I've worked quite a lot with raw decoding with various type of cameras and I haven't seen any indications of non-linearity. There are cameras that use a static curve to encode raw data (efficient compression), but it's reversed when decoding the format, so again no effect on camera profiling.
It's true that we will measure the product of the color filters, ADC, on-chip noise reduction and any firmware tweaks, but that is what we want anyway, we want to measure the response the color conversion pipeline will see.
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if he has used any public measurement data.
I got it from public database: http://www.cis.rit.edu/jwgu/research/camspec/db.php
BTW, if someone can make measurements of sensors for cameras that isn't this list, then I can make corresponding profiles. Absolutely for free. =)
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Okay, sorry for being away for so long, but I've had a reason: I've written a new camera profiling tool, and now I just made the first release. See what it can do at its web page: http://www.ludd.ltu.se/~torger/dcamprof.html
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Okay, sorry for being away for so long, but I've had a reason: I've written a new camera profiling tool, and now I just made the first release. See what it can do at its web page: http://www.ludd.ltu.se/~torger/dcamprof.html
thank you !
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I've been reading this thread and have one question:
Why do you want to profile a camera? For a science project, I understand. But why would a photographer want dead accurate color? After all, who shoots with dead accurate light?
Isn't the best color for the image what we should be seeking?
I understand prints matching the display, but matching Mother Nature? I don't get it.
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I've been reading this thread and have one question:
Why do you want to profile a camera? For a science project, I understand. But why would a photographer want dead accurate color? After all, who shoots with dead accurate light?
Isn't the best color for the image what we should be seeking?
I understand prints matching the display, but matching Mother Nature? I don't get it.
some folks consider that they want to start their own color adjustment from that "accurate" color rather then from what OEM profiles deliver
some folks just want a "different" color vs OEM profiles
some folks consider that OEM profiles are simply not good enough, guide color transforms incorrectly with saturated colors, light emitting sources, etc
if you are happy with the color from OEM profiles as 99% users are then just move on
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I've been reading this thread and have one question:
Why do you want to profile a camera? For a science project, I understand. But why would a photographer want dead accurate color? After all, who shoots with dead accurate light?
Isn't the best color for the image what we should be seeking?
I understand prints matching the display, but matching Mother Nature? I don't get it.
To me it's about artistic integrity. I want to have my own personal style of color which I have control of and know how I deviate from realism. With digital cameras color reproducition can be much more accurate than it ever could with film. This fact is greatly under-utilized, most raw converters are stuck in a film thinking and their profiles is part of that - profiles deliver a "look" just like film did. In addition color adjustments possibilities are often a bit limited and coarse, like in Lightroom, as you're supposed to embrace the look of Adobe via their profiles rather than make your own look. The profile don't tell you how it changes the color, it just does it.
While it's a great approach for laymen or those that are not that into color, I don't like this approach. I want to make the look from scratch according to my taste and my eye for color, and the logical starting point for that is a neutral profile.
There is of course no thing like absolute accuracy, and when shooting landscape the light changes greatly. But the scale of which typical bundled profiles distorts color to acheive a look(tm) is so huge that light variations is just a breeze in comparison.
I do agree that we should be seeking the best color for the image, I just think that flipping through a bunch of manufacturer pre-defined looks is not the way to go for me. Another aspect is that when working with neutral profiles I think you get a deeper understanding of how colors work in a scene, what an image requires. I think that enriches the artistic side of my photography.
It's highly personal though, and I don't say using predefined manufacturer looks is wrong, I just don't think it's the right way for me and I think many other would appreciate this way to work too. Unfortunately the typical tools available have not made this way to work very easy, so it's little bit of a special interest of the few, and my technical DCamProf software won't change that unfortunately. It will help those with that special interest though.
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To me it's about artistic integrity. I want to have my own personal style of color which I have control of and know how I deviate from realism. With digital cameras color reproducition can be much more accurate than it ever could with film. This fact is greatly under-utilized, most raw converters are stuck in a film thinking and their profiles is part of that - profiles deliver a "look" just like film did. In addition color adjustments possibilities are often a bit limited and coarse, like in Lightroom, as you're supposed to embrace the look of Adobe via their profiles rather than make your own look. The profile don't tell you how it changes the color, it just does it.
While it's a great approach for laymen or those that are not that into color, I don't like this approach. I want to make the look from scratch according to my taste and my eye for color, and the logical starting point for that is a neutral profile.
There is of course no thing like absolute accuracy, and when shooting landscape the light changes greatly. But the scale of which typical bundled profiles distorts color to acheive a look(tm) is so huge that light variations is just a breeze in comparison.
I do agree that we should be seeking the best color for the image, I just think that flipping through a bunch of manufacturer pre-defined looks is not the way to go for me. Another aspect is that when working with neutral profiles I think you get a deeper understanding of how colors work in a scene, what an image requires. I think that enriches the artistic side of my photography.
It's highly personal though, and I don't say using predefined manufacturer looks is wrong, I just don't think it's the right way for me and I think many other would appreciate this way to work too. Unfortunately the typical tools available have not made this way to work very easy, so it's little bit of a special interest of the few, and my technical DCamProf software won't change that unfortunately. It will help those with that special interest though.
Thanks for the thoughtful reply!!!
But, I don't think I'll take this approach. It's not for me :)