Image processing/restoration in Matlab

Question

I have several images that i would like to correct from artifacts. They show different animals but they appear to look like they were folded (look at the image attached). The folds are straight and they go through the wings as well, they are just hard to see but they are there. I would like to remove the folds but at the same time preserve the information from the picture (structure and color of the wings). I am using MATLAB right now and i have tried several methods but nothing seems to work.

Initially i tried to see if i can see anything by using an FFT but i do not see a structure in the spectrum that i can remove. I tried to use several edge detection methods (like Sobel, etc) but the problem is that the edge detection always finds the edges of the wings (because they are stronger) rather than the straight lines. I was wondering if anyone has any ideas about how to proceed with this problem? I am not attaching any code because none of the methods i have tried (and described) are working.

Thank you for the help in advance.

Answer 1

I'll leave this bit here for anyone that knows how to erase those lines without affecting the quality of the image:

a = imread('https://i.stack.imgur.com/WpFAA.jpg');
b = abs(diff(a,1,2));
b = max(b,[],3);
c = imerode(b,strel('rectangle',[200,1]));

Answer 2

I think you should use a 2-dimensional Fast Fourier Transform It might be easier to first use GIMP / Photoshop if a filter can resolve it.

I'm guessing the CC sensor got broken (it looks to good for old scanner problems). Maybe an electric distortion while it was reading the camera sensor. Such signals in theory have a repeating nature. I dont think this was caused by a wrong colordepth/colorspace translation

If you like to code, then you might also write a custom pixel based filter in which you take x vertical pixels (say 20 or so) compare them to the next vertical row of 20 pixels. Compare against HSL (L lightnes), not RGB. From all pixels calculate brightness changes this way.
Then per pixel check H (heu) is within range of nearby pixels take slope average of their brightness(ea take 30 pixels horizontal, calculate average brightnes of first 10 and last 10 pixels apply that brightness to center pixel 15,... //30, 15, 10 try to find what works well

Since you have whole strokes that apear brighter/darker such filter would smooth that effect out, the difficulty is to remain other patterns (the wings are less distorted), knowing what color space the sensor had might allow for a better decision as HSL, maybe HSV or so..