Suppose we have a sequence of still images each of which has been contaminated by some particles(ex, dust/sand/smoke) making the images very poor in certain areas.

What architecture would be best to teach image regeneration using multiple frames? The simplest technique is to simply find a way to detect what parts of the image are contaminated and uncontaminated and pull uncontaminated sections from each frame.

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    $\begingroup$ I don't know a lot about it, but I think the technique is called Video Inpainting and you can find a lot of papers by searching the topic. And I was easily able to find review papers on this topic $\endgroup$
    – amin
    Oct 25 '20 at 12:23
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    $\begingroup$ We have denoising autoencoders to remove noise so we can use the difference between original and denoised picture to define areas with good or bad quality. After that, either segmentation or clustering algorithms can be used to determine the exact areas with bad quality. $\endgroup$ Oct 28 '20 at 9:00

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