Hi all,

I see that a lively discussion was started by my mail.
I’ll try to combine as many replies into one single e-mail as possible.

1. The trees and branches as test image: the colour artifacts in this image are 
larger areas, not just one or two pixels (like in the black tie). This makes it 
more difficult to treat them via noise reduction. That’s one reason I chose 
this image for torture testing.

2. All the new test images from the X70: thanks a lot for these, they are great 
for testing! I’m still busy with the bird at this time, but I’ll go through 
them one by one as soon as I find some time.

3. The bird image: this is very interesting and revealing! I have a prototypic 
implementation of my algorithm in matlab (slow and can handle only very small 
images). I took your OOC JPEG, mosaiced, and demosaiced the most critical part 
of the bird again. No problematic dots, see ‚bird_matlab‘ in the usual dropbox 
location. Bird_ml_test shows a CPSNR of 42.48 dB. Folks dealing with 
demosaicing might identify this as a very respectable value for a difficult 
image area. So my conclusion is that the problem is not with my algorithm per 
se, but with my openCL implementation. I continue working on this topic for the 
time being. As it appears to be only the implementation and not the algorithm 
per se it _must_ be solvable.

4. My contrast curve and colors: I know it’s everything but ideal, but it was a 
quick and dirty way to get an ‚infrastructure‘ for my implementation by using 
dcraw. For the time being, this is also my best way of continuing the tests, 
until I get something more evolved. 

5. This brings me to the question of Dan: yes, it should be possible to get my 
algorithm into darktable to enable a broader range of testing. This is 
ultimately still my goal. I’m just not there yet, so please be a bit patient, 
especially since this is just a little hobby of mine. I’m not a programmer (at 
least not in the classical sense) by profession, and all I know about 
demosaicing is self-taught. However, after re-checking the bird image as 
described above, I’m quite confident things are moving into the right direction.

Cheers,
Ingo




> Am 29.04.2016 um 02:11 schrieb J. Liles <malnour...@gmail.com>:
> 
> 
> 
> On Wed, Apr 27, 2016 at 5:14 PM, J. Liles <malnour...@gmail.com 
> <mailto:malnour...@gmail.com>> wrote:
> 
> 
> On Wed, Apr 27, 2016 at 3:36 PM, J. Liles <malnour...@gmail.com 
> <mailto:malnour...@gmail.com>> wrote:
> 
> 
> On Wed, Apr 27, 2016 at 1:53 PM, J. Liles <malnour...@gmail.com 
> <mailto:malnour...@gmail.com>> wrote:
> 
> 
> On Wed, Apr 27, 2016 at 11:56 AM, J. Liles <malnour...@gmail.com 
> <mailto:malnour...@gmail.com>> wrote:
> 
> 
> On Wed, Apr 27, 2016 at 11:49 AM, johannes hanika <hana...@gmail.com 
> <mailto:hana...@gmail.com>> wrote:
> [..]
> 
> > You've lost the color of the sunset on the lettering on the clock face
> > though.
> 
> oh, i bet that's the classic chrome film style. i just applied one
> from the list to get a fuji-like tonecurve, since those affect
> saturation of colours as well as the contrast a lot.
> 
> > This is not the best test scene because it doesn't appear to actually
> > contain any vibrant colors.
> 
> i think for a certain kind of artefact it's just fine.. these fine
> branches in front of a brighter sky already produce quite terrible
> colour fringes (if i turn of the denoising that is).
> 
> > A better scene would have real green, magenta
> > and cyan objects, preferably with fine patterns. That would make it more
> > apparent when the processing is not producing color artifacts vs. just
> > smoothing all of the colors.
> 
> the thing is, this sensor cannot capture colour information beyond a
> certain frequency, because the red/blue pixels are spaced so wide
> apart from each other.
> 
> 
> True, but I'm inclined to use the Fuji camera generated JPGs as a baseline 
> for that: A minimum amount of luma and chroma resolution. With my Bayer 
> images, I can get much more detail out of them by processing the RAWs in 
> Darktable comparted to what the camera JPGs contain.
> 
> I should think that the same should be true of X-Trans, since in-camera 
> processing is presumably optimized for speed rather than quality. 
> 
> We always need to reference to the camera JPGs... If the RAW processing is 
> producing less color detail than the JPG, then there's still room for 
> improvement (and probably a lot of it).
>  
> 
> 
> I've added a third image to the problem image set at:
> 
> http://www.nevermindhim.com/fuji-xtrans-samples 
> <http://www.nevermindhim.com/fuji-xtrans-samples> 
> 
> I wanted to include both a subject prone to demoasicing artifacts and 
> subjects with fine color detail in the same image.
> 
> If you play around with it in DT, I think you'll find that any setting that 
> eliminates the color artifacts on the black tie will smear the color of the 
> other ties, which does not happen in the camera JPG.
> 
> 
> Replying to myself again... Actually with a bit more tweaking and a different 
> approach (which is actually similar to the approach that I use to denoise 
> high ISO Bayer images), I've been able to pretty closely match my third 
> problem image camera JPG in DT. The same style applied to Ingo's backlit tree 
> image also looks quite good. No discernable color artifacts in the branches 
> (even with saturation cranked to the maximum) without washing out the color 
> in other image areas. You'll notice in my sample #3 that even the Fuji JPEG 
> engine leaves a blob of a magenta artifact on the tie... I didn't attempt to 
> take it any fruther.
> 
> Here's the style:
> 
> http://www.nevermindhim.com/files/fuji-xtrans-samples/X-Trans%20II%20Denoise%20200.dtstyle
>  
> <http://www.nevermindhim.com/files/fuji-xtrans-samples/X-Trans%20II%20Denoise%20200.dtstyle>
> 
> Even though it says 200, it seems to work pretty well on higher ISOs (up to 
> 3200), but those images could probably use a little luma denoising too.
> 
> I can't post sample output for the backlit tree image because DT crashes when 
> exporting that one for some reason.
> 
> 
> I'm now less concerned about the color artifacts, as it seems that denoising 
> can in fact clean them up without causing too much smearing (not more than 
> the in-camera JPGs anyway).
> 
> But what about the grid/speckles?
> 
> I've put a gimp XCF here with two layers in it (warning: 100MB download):
> 
> http://www.nevermindhim.com/files/fuji-xtrans-samples/bird.xcf 
> <http://www.nevermindhim.com/files/fuji-xtrans-samples/bird.xcf>
> 
> By toggling the visibility of the top layer, perhaps you can see what I'm 
> referring to. I have some other images which exhibit this also. Adding enough 
> luminance NR to remove these speckles completely obliterates detail. 
> 
>  
> 
> 
> I've added 4th problem image to the set at:
> 
> http://www.nevermindhim.com/fuji-xtrans-samples 
> <http://www.nevermindhim.com/fuji-xtrans-samples>
> 
> I think it does a slightly better job of including fine monochrome detail and 
> fine color detail in the same image.
> 
> I've also updated my styles. I've gone back to using the equalizer, as the 
> styles using the bilateral chroma denoise were producing some color halo 
> effects. 
> 
> I've also stopped using the color smoothing option on the demosaic module, as 
> it turned out to be smearing fine color detail at any setting other than off 
> (in a way that I could avoid by doing all the color smoothing in the 
> equalizer module)
> 
> For a good example of this, look at the guy's pink hair in image #2. The 
> camera JPG retains some detail there which I could not match with color 
> smoothing enabled.
> 
> I'm not sure how much more sophsticated Fuji's algorithm could be, but I 
> suspect it is indeed doing something to reduce these color artifacts in the 
> demosaicing stage, because it's extremely difficult to remove them later 
> blurring the high frequency color detail.
> 
> I wonder how many of the proprietary raw processors also produce the 
> grid/speckle artifacts... That seems to be a tricky one. It's very 'digital' 
> looking.
>  
> 
> 
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