Leica M9 Serious contender?

[telyt]

Whether aliasing is visually objectionable depends heavily on the subject matter. For most natural subjects (like the stuff you shoot, judging by your web site), a modest amount of aliasing can be visually indistinguishable from enhanced sharpness and detail. But for some subjects, particularly cloth and other man-made objects that have regular, repeating patterns, aliasing an be a serious problem.

Fine feather detail has many regular repeating patterns.  The most difficult bird to photograph for me have been the California Quail and Gambel's Quail; their back and chest feathers cause the wildest aliasing and color moire I've yet seen.  However the AA filter doesn't solve the problem.  These birds' feathers also cause color moire and aliasing when using a camera with an AA filter.

[ErikKaffehr]

Hi,

If you look at test images with USAF type test targets it's quit obvious that there is aliasing even in AA-filtered images. The amount can vary with converter. Like most things in life the AA-filter is a compromise.

Erwin Puts compares some raw converters here:
http://www.imx.nl/photo/leica/camera/page165/page165.html

Erwin Puts also have some samples showing color Moiré

here: http://www.imx.nl/photo/leica/camera/page1...s/m9100sela.jpg (Leica M9)

and here: http://www.imx.nl/photo/leica/camera/page1...les/d3xsela.jpg (Nikon D3x, still has some)

With the full article here: http://www.imx.nl/photo/leica/camera/page157/page157.html

Interestingly he has not seen any Moiré on the Leica M8 in the same test. Basically the M8 and the M9 share sensor, so it's a bit odd that the Moiré is not showing up. I'm often not certain what Erwin Puts writes about his experiments, like distance and cropping.

Best regards
Erik

Fine feather detail has many regular repeating patterns.  The most difficult bird to photograph for me have been the California Quail and Gambel's Quail; their back and chest feathers cause the wildest aliasing and color moire I've yet seen.  However the AA filter doesn't solve the problem.  These birds' feathers also cause color moire and aliasing when using a camera with an AA filter.

[ErikKaffehr]

Sorry Bernard, which images?

I presume that M9 and S2 users are expected to shoot "raw", if you say that "raw" images are manipulated than the value of having "raw" would be much reduced. Post processing is another issue. In the Video on S2 they photographers discuss that the S2 images are less tolerant of sharpening than the corresponding Phase One back.

One issue here is microlenses. Microlenses increase the fill factor and the fill factor is also effecting aliasing. Making the "sensel" larger increases the probabilty that a ray of light is affecting more than one pixel.

Best regards
Erik

Yes indeed. I would add one thing to this, images from AA filterless cameras typically have undergone some form of in camera processing to reduce artifcats (the M9 and S2 come to mind), that are also easy to recognize and can be perceived as being pleasing or not. I would describe this look as micro-level painterly.

Cheers,
Bernard

[Plekto]

... look at images from Foveon X3 sensors of resolution test charts, where the number of line pairs changes as the line pairs get closer together, while still showing sharp black and white alternation instead of more gracefully and honestly blurring to gray. Gray is an honest "I don't know" whereas aliasing can answer a confident "black" at a place where the correct answer is "white": sharpness with no connection to reality.

It is another question, more esthetic than technical, how often and how badly this aliasing actually harms the final "print image quality".

That's the interesting thing, though.  Our eyes hate random noise and digital artifacts more than they dislike slightly blurry and off-color images. This is also why tube amps sound better than transistors to most people - the nature of the distortion, when it does happen, is more pleasing to our senses.  When it doesn't, it's a moot point in either case(and it won't 95%+ of the time).   But when it does, well, things get hairy fast with digital, be it audio or optical.

I find that non-Bayer type sensors produce a better image because they cause errors that our brains process as "correct" looking.  In that resolution test, for instance, our brains expect there to be detail and a line still present and not random gray.   I find this to be most obvious in grass and other repeating semi-random patterns found in nature.  

That said, the Fuji method as well as their diagonal alignment creates far less issues than either the Foveon or Bayer designs.  I just with it had a few more pixels in HDR/high quality mode.  Because what it does with the 6MP it has is amazing.

[joofa]

OK, great. Explain how, if you are sampling the image at 50 lp/mm (Nyquist frequency) or 100 pixels/mm (Nyquist rate), you can sample a 75 lp/mm input signal (which is going to alias down to 25 lp/mm) and reliably distinguish the 25 lp/mm aliased signal from a non-aliased signal that was 25 lp/mm before sampling? How you can transform an aliased 25 lp/mm signal back to 75 lp/mm without taking any un-aliased 25 lp/mm signal along for the ride? How does a DSB (dual-sideband modulator?) help solve this problem when the only data you have to work with is the sampled signal?

A sampled data system has periodicities that can be taken advantage of here. I already said that aliasing spectrum can be canceled using these periodicities.

If what you are saying is valid, I should be able to take an un-aliased image 1000 pixels square, downsample it to 750 pixels using nearest-neighbor resampling (so that no anti-aliasing filtration is done), and then run some kind of software transform on the image to expand it back to 1000 pixels with little or no distortion or loss of detail.

Software transform? When did I say that? You need a little background in communication systems to understand some of this stuff.

[Jonathan Wienke]

A sampled data system has periodicities that can be taken advantage of here. I already said that aliasing spectrum can be canceled using these periodicities.

Yeah, you keep SAYING that, but you have yet to offer one shred of evidence that it can be done in real-world conditions that have any relevance whatsoever to digital imaging.

Software transform? When did I say that? You need a little background in communication systems to understand some of this stuff.

You're right, you didn't mention software, I did. I have a lot deeper background in the subject than you might think; I used to be very active in CB radio and understand the difference between frequency modulation, amplitude modulation, single sideband modulation, etc. and I've designed and built a variety of electronic devices. I'm also a fairly decent musician; I've been playing various instruments for about 30 years, and have been recording and mixing sound for about 15. I'm familiar with modulation effects, and know that frequency modulation, amplitude modulation (including single- and double-sideband variants) and all kinds of similar things can be implemented in software as well as hardware. You can get all kinds of stuff like that as plug-in modules for audio editing software like ProTools, Adobe Audition, etc.

IF your theory is applicable to digital imaging, than it can be implemented in software, and that software can be used to process images from digital cameras without AA filters (or at least having weaker-than-normal filters) to remove aliasing artifacts without disturbing image detail. To quote your esteemed scientific colleague Warren Mars, "put up or shut up"--either explain HOW aliasing might be removed from a digital image under the conditions you described earlier according to your theory, or STFU and quit wasting LL's bandwidth. Don't be afraid to use big words, I can handle it.

I've already posted an image that contains the kind of aliasing you described; the aliasing it contains exactly splits the difference (logarithmically) between the Nyquist rate and Nyquist frequency. If you can reconstitute it back to its 512x512-pixel size in a manner that closely matches the original image, then congratulations; you have something that can be used to approximately double the linear resolution of any digital sensor. If not, then I'm calling BS on yet another internet crackpot.

[joofa]

To quote your esteemed scientific colleague Warren Mars, ... or STFU and quit wasting LL's bandwidth. ...  I'm calling BS on yet another internet crackpot.

I'm sorry Jonathan the communication is over. You have esteemed qualifications as you report but I have to spend hours sometimes researching some topic before I summarize it in a few lines for internet forums and I just don't feel compelled to do that right now.

[Jonathan Wienke]

I'm sorry Jonathan the communication is over. You have esteemed qualifications as you report but I have to spend hours sometimes researching some topic before I summarize it in a few lines for internet forums and I just don't feel compelled to do that right now.

Why don't you simply post a link to a scientific paper describing this de-aliasing technique if this has been published somewhere? I don't need a layman's summary; for most stuff I can look at the nitty-gritty technical details and figure it out with a bit of study. Surely that wouldn't require hours of effort on your part...

[Jonathan Wienke]

[crickets]...

[Plekto]

I just bracket and blend with the Zero Noise program that's linked in the discussion in this forum.  It solves most of the ills in one step.

[Jonathan Wienke]

Given that Joofa has posted at length on the subject of aliasing removal on several fora without ever posting anything of substance to support those claims, and hasn't bothered to respond since I challenged him to prove his claims (even though he's posted several times since then), I'm going to go ahead and conclude he can't back up his claims with any substance.

[telyt]

... I'm going to go ahead and conclude he can't back up his claims with any substance.

Your assumption is going to make an ass out of u (but not me).  Have you ever actually seen a print made from an M8, M9, or DMR?  Look at my web images for the last 3.5 years and tell me which one would have been better if I had used a camera with an AA filter.  I know of one photo on my website in that time period that is visibly degraded by aliasing.  The fine feather detail of that same bird also causes aliasing when photographed with a camera that has an AA filter.

Of course aliasing is false data.  So is the AA filter's blur, and the USM required to restore microcontrast to an AA-filtered photos.  It's all an illusion - the question is, if you have to be an anal-retentive pixel-peeper to see the difference, does the question deserve the bandwidth that has been devoted to it here?  Look at my prints and tell me the lack of an AA filter is a problem.  You know where to find them.

[Jonathan Wienke]

Your assumption is going to make an ass out of u (but not me).

The issue of whether aliasing is visually tolerable in an image is entirely separate from the question of whether it can be removed without destroying real image data. I've already posted examples of both cases--where aliasing looks OK in an an image, and where it looks really bad. I have no argument with your contention that you can make visually attractive images with captures from a camera with no AA filter.

But as I said before, that is not a universal truth. In some circumstances, aliasing can cause visually jarring artifacts that are not acceptable, and notwithstanding Joofa's assertions to the contrary, there is no way to remove them without taking out real image detail. There some situations where an AA filter is not necessary, and other situations where it is.