what reason could make the noise/effect in this image?
Below is the original
Thanks!
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$\begingroup$ Interesting. It looks like a texture was superimposed on the image. Nothing distinctive pops up in the spectra. Wild guess, if it was a process: fractional Wiener sheets. $\endgroup$ – Maurits Mar 24 '15 at 21:42
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$\begingroup$ I think certain phase components have been missing/removed in the frequency domain. $\endgroup$ – That-Kickass-GirL Apr 26 '15 at 5:18
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$\begingroup$ SE.DSP wishes you a happy new year 2017, with a kind reminder that your question and its answers may require some action (update, votes, acceptance, etc.) $\endgroup$ – Laurent Duval Dec 31 '16 at 17:09
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$\begingroup$ Your question has beeen answered. Do not hesitate to vote for the useful ones and accept the most suitable $\endgroup$ – Laurent Duval Feb 9 '17 at 17:17
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Looking at it, my thought is that the top image has been printed out (onto poor quality paper), then later scanned. The artefacts would then be a mixture of paper texture and poor printing. It could also include ink transfer from the facing page (if part of a book or newspaper, and/or bleed-through from something printed on the back of the paper.
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If you crop the distorted image to remove the white border, you get an image with an aspect ratio of $1:1.5$ ($512\times683$ instead of $768\times1024$). So you have undersampling noise, potentially aliasing, because a proper resampling should have smoothly interpolated the original. I am pasting these versions in false color, to better emphasize artifacts.
From the images above, you can see color changes in flat/smooth areas, such as the sky above the wire, or the inter-road track orange. So a plausible background bias, with at least a relatively low-frequency part: look at the vertical orange-red-orange transition above the wires, with a period of around $1/3$ of the image width.
The original is jpeg-compressed with a unity quantization table (100% quality), the rescaled and white-bordered was jpeg-compressed with much lower quality (75%), which you can see from blocking artifacts in a 7-pixel frame around the image. You can verify the details, using for instance JPEGsnoop:
a detailed JPEG image decoder and analysis tool. It reports all image metadata and can even help identify if an image has been edited
Then we can look at gradients:
or Fourier spectrum (average removed, windowed):
So, the gradient is noisier, and coarser, and the Fourier spectrum looks similar, only noisier and equalized. I doubt about the hypothesis of a paper scan at a lower resolution. However, the color fluctuation and the stripped-noise patterns reminds me of patterns one can observe when reconstructing image from phase and magnitude (from SE.DSP Recover image by only magnitude of image fourier transform)
So a possibility: the original image was downsampled by a $3/2$ ratio in the Fourier domain, and reconstructed without too much care.
I would be glad to get image expert feedback in this wild guess.
answered Nov 5 '16 at 15:45
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Perlin? Though to me it looks like a poor nearest-neighbor interpolation, after up-down resampling. I'm just replying with a guess, I admit.
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$\begingroup$ I agree with interpolation error and bad up-down resampling, we can clearly see aliasing on the noisy image. Image has been saved with a bad resolution, then upsampled probably for displaying issues, some informations have been lost and the interpolation after up sampling is bad. $\endgroup$ – Antoine Bassoul Apr 26 '15 at 18:44
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First, there is for sure a poor up-down sampling / interpolation that cause some aliasing. I don't know for the wild superimposed texture. My guess would be a bad inverse radon transform, but it is very unlikely in a photography context ... Maybe it is compression artifact from a ridgelet transform.
Area 2 is clearer than it should be while right and left side are darker, as if mean along columns had corrupted every rows.
In area 1 we can see line shaped artifacts, it makes me think about radon transform stuff.
There is also a clear loss of contrast
