问题
I'm looking for an algorithm (ideally a C/C++ implementation) that calculates perceived similarity between two images, taking into account psychovisual factors (e.g. that difference in chroma is not as bad as difference in brightness).
I have original image and multiple variations of it (256-color quantisations in my case) and I'd like algorithm to find which image a human would judge as the best one.
The best I've found so far is SSIM, but it doesn't "understand" dithering (error diffusion) and implementation uses linear RGB (I've fixed that by implementing my own).
Alternatively, it could be algorithm that preprocesses images for comparison with SSIM/PSNR/MSE or other typical algorithm.
回答1:
Well. Can't you turn it into an online job with amazon's mechanical turk? Or make a game of it like google image labeler? You can give extra points, or payment if people agree on their scores.
The reason is I think this job is just too difficult for a computer. SSIM can't score dithered images, and if you smooth the image, to make it work with SSIM, the dither pattern can't be part of the quality judgement, because it is no longer present in the image. And that pattern is probably relevant for image quality.
来源：https://stackoverflow.com/questions/4298422/psychovisual-image-similarity-algorithm-library