Author Topic: [1.8RC1 Win64] a Deconvolution issue  (Read 3942 times)

Offline Bart_van_der_Wolf

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[1.8RC1 Win64] a Deconvolution issue
« on: 2013 January 06 14:02:45 »
Hello,

I'm a new user of PixInsight, and have updated the 1.8RC1 with the latest updates available. I've encountered an issue that was not present in the latest 1.7 release. When I deconvolve a regular RGB image of a terrestrial object, with automatic CIE Y channel targeting, I now get horrible Magenta edges (as if it were Chromatic Aberration) and Green shadow areas.

When I first extract an L channel image instead of the CIE Y channel, deconvolve that, and then Combine that channel with the RGB image again, everything work out as expected, no strange colors. It seems like the automatic CIE Y channel target selection for an RGB image doesn't function like it did in version 1.7.

BTW, manually extracting the CIE Y channel in version 1.7, deconvolving and then combining it with the RGB image also produced the magenta edges, unlike the automatic CIE Y targeting in the V1.7 Deconvolution Process.

I've also tried converting the Sample format to 64-bit floating point, but that didn't solve the issue. Changing the Gamma didn't help either.

I know this is a Release Candidate and not a stable release, but with this message I also wanted to alert people to look out for this changed behavior. I have searched the forum and found no other mention of it.

Kind regards,
Bart

Offline Bart_van_der_Wolf

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Re: [1.8RC1 Win64] a Deconvolution issue, continued
« Reply #1 on: 2013 January 09 06:23:48 »
Here I'll add an example of what's happening:

This is an artificial (CGI) image of the center of a resolution test target:

I open the file with PixInsight 1.8RC1, and disable Color Management. Color Managed images show the same issue, so it doesn't seem relevant in this case.

I also open the following image of a Gaussian Blur with a 1.0 radius PSF, also with Color Management disabled:

This Gaussian Blur PSF will be used to first Convolve the image with, and then to Deconvolve the blurred image. I use
Process|Convolution|Convolution and on the Image tab I select the 'PSF010-pointsampled' image as filter image, and Apply the convolution to the 'SinusoidalSiemensStar_500px' image. Sofar, all is well.

I now open the Process|Deconvolution|Deconvolution process on the External PSF tab,
and select the 'PSF010_pointsampled' image as kernel.

I used 100 iterations to improve the Richardson-Lucy restoration, and make the issue a bit more visible, although it also shows up at 10 iterrations. Since this is a CGI image source there is no noise other than quantization rounding errors, and therefore Wavelet Regularization was switched off. In regular camera images with noise, and Regularization switched on, the effect is the same.

This produced the following result, with the same magenta artifacts I see on other images:

Do note, that PixInsight 1.7 didn't produce this artifact with the same settings. The only way to avoid it in 1.8RC1 is to target the RGB/K components individually instead of the default Luminance (CIE Y), or first create a separate CIE L channel, deconvolve that, and recombine it with the original RGB image. Both 'workarounds' are less efficient, obviously.

Hope that helps to identify the cause.

Kind regards,
Bart

Offline Juan Conejero

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Re: [1.8RC1 Win64] a Deconvolution issue
« Reply #2 on: 2013 January 10 15:21:22 »
Hi Bart,

Thank you so much for detecting this serious regression in PI 1.8.0 RC1. I've got good news: this bug is already fixed in version 1.8.0 RC2, which I'll release this weekend.

Again, thank you for your support.
Juan Conejero
PixInsight Development Team
http://pixinsight.com/

Offline Bart_van_der_Wolf

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Re: [1.8RC1 Win64] a Deconvolution issue
« Reply #3 on: 2013 January 11 05:02:01 »
Hi Bart,

Thank you so much for detecting this serious regression in PI 1.8.0 RC1. I've got good news: this bug is already fixed in version 1.8.0 RC2, which I'll release this weekend.

Again, thank you for your support.

Hi Juan,

It's my pleasure to be of help. I'm looking forward to the update, and would like to thank you and the team for a great piece of software.

Cheers,
Bart