Please help with Argyll scanin

[GWGill]

The tif was downscaled to 1/4 the size, and Argyll placed the frames (or what they're called)  partly outside the actual color patches.

If the image you included is that case, then I'd suspect that the 7 pieces of white tape have completely thrown the recognition off.

[GWGill]

Well what he showed me was that the .ti3 file can be read and written with just any text editor. Adding a line with black values of zero, and increasing the 'number of  data sets' accordingly will enable the production of pure black. Without this, the blackest black the profile can produce is the blackest black of the target. In principle, absolute black should be possible, too. This is as I understood it.

That assumes that the camera sensor is perfectly zero'd. This isn't always the case.

[GWGill]

what it does practically (I think) it just makes sure that black point tag in icc container is set to all zeroes - and you can simply modify the icc profile directly...

Note that the black point tag is simply annotation - it has no effect on the actual profile itself.

[AlterEgo]

That assumes that the camera sensor is perfectly zero'd. This isn't always the case.

but let us assume that we have such perfect camera with such sensor - how does that virtual black patch (RGB(0,0,0) -> RGB (0,0,0)) is going to alter a simple matrix being generated ?

[GWGill]

but let us assume that we have such perfect camera with such sensor - how does that virtual black patch (RGB(0,0,0) -> RGB (0,0,0)) is going to alter a simple matrix being generated ?

It will have a weighting in the matrix fit of the sample points.

[AlterEgo]

It will have a weighting in the matrix fit of the sample points.

I tried twice and and it did not change anything at all (except bkpt tag)... and how come (0,0,0) -> (0,0,0) shall change anything at all mathematically when you calculate a matrix ? again zero vector * any matrix = zero vector, it shall not by that fact affect the fitting... am I missing something ? if you say it shall have a weighting in how Argyll code does calculate matrix (colprof -am) then why the matrices are the same with and without black patch in .ti3

inserting black point in .ti3 like this

...
SAMPLE_ID SAMPLE_NAME RGB_R RGB_G RGB_B LAB_L LAB_A LAB_B
...
265 "GS00" 0.0 0.0 0.0 0.0 0.0 0.0
...

no changes vs pref. profile

[Hening Bettermann]

> If the image you included is that case, then I'd suspect that the 7 pieces of white tape have completely thrown the recognition off.

Yes but only because scanin placed the frames on them, outside the actual target. With the target image downscaled to 1/2 instead of 1/4, the diag.tif looked different and worked. It looks to me like scanin wants a certain fixed minimum size for the target image.

> That assumes that the camera sensor is perfectly zero'd. This isn't always the case.

Sure, but that is beyond my control. But apart from that, my understanding is correct, or at least in accordance with yours? If so, I don't understand how the two following statements relate to each other:

> Note that the black point tag is simply annotation - it has no effect on the actual profile itself.


> It will have a weighting in the matrix fit of the sample points.

I imagine the latter translates to that the 0 black point lifts the shadows? (if it does anything at all).

[GWGill]

I tried twice and and it did not change anything at all (except bkpt tag)... and how come (0,0,0) -> (0,0,0) shall change anything at all mathematically when you calculate a matrix ?

Yes you're right that for a pure matrix profile, 0,0,0 -> 0,0,0 won't change anything. So why add it ?
For any sort of profile that models an offset though, it will change things.

[GWGill]

> If the image you included is that case, then I'd suspect that the 7 pieces of white tape have completely thrown the recognition off.

Yes but only because scanin placed the frames on them, outside the actual target.

It's setup to recognize rectangular patches, and bits of white tape look very much like high contrast rectangular patches. It doesn't have an ability to recognize general objects like frames (it's not A.I.), but will tend to ignore anything that doesn't look like rectangular patches.

With the target image downscaled to 1/2 instead of 1/4, the diag.tif looked different and worked. It looks to me like scanin wants a certain fixed minimum size for the target image.

It's size independent. Too low a resolution and it will fail (won't be able to detect edges, and/or not enough pixels in a patch), too high also risks not detecting edges and noise being detected as edges, but there is a very wide margin in between.

But apart from that, my understanding is correct, or at least in accordance with yours?

Adding such a patch fundamentally defeats the purpose of characterizing the device. If you already know/assume that zero maps to zero, why are you measuring it ? That's not to say it's always wrong, but be aware of what it implies.

If so, I don't understand how the two following statements relate to each other:

> Note that the black point tag is simply annotation - it has no effect on the actual profile itself.

> It will have a weighting in the matrix fit of the sample points.

If you edit the profile and change the black point tag, the way the profile says the device behaves doesn't change.
If you add a test point saying that perfect black measures as RGB=0 by the device, then this will have an effect on the cLUT/matrix/shaper model that colprof will create (except the special case of a matrix only profile, in which case there is no point in adding such a patch value).

I imagine the latter translates to that the 0 black point lifts the shadows? (if it does anything at all).

Its effect will depend on how the device actually measures or is extrapolated to measure perfect black. It may lift or reduce or make no change to the shadows.

[AlterEgo]

Yes you're right that for a pure matrix profile, 0,0,0 -> 0,0,0 won't change anything. So why add it ?

that was not my idea - I just wondered as to why the topic starter, Hening B., did this for his pure matrix profile, he ref'd to something that Brian G, the author of Iridient raw converter told him and I was trying to find out why and what... I can imagine may be how this can be useful for LUT profiles for example, where naturally RGB(0,0,0) might be mapped to who knows where and you may be might add some virtual data to .ti3 to make sure that mapping is closer to what you want it to be in such areas, to bend that way the 2.x-3D LUT which otherwise might not be calculated properly - am I right ... and I found apparently the source of that exercise = http://www.freelists.org/post/argyllcms/Camera-matrix-profile-adding-ti3-perfect-white-data-set

[Hening Bettermann]

It may very well be that Brian gave his advice with regard to LUT profiles, and the ignorant transfer to a matrix-only profile goes on my account.