Interested readers can follow this approach to train detectors for other domains—even general-purpose ones. Build an AIGC detector for academic papers, slap on a flashy frontend, and sell it as an “AI plagiarism checker” to clueless undergrads. If you make money, don’t forget to donate a little.
Another way to look at our threshold matrix is as a kind of probability matrix. Instead of offsetting the input pixel by the value given in the threshold matrix, we can instead use the value to sample from the cumulative probability of possible candidate colours, where each colour is assigned a probability or weight . Each colour’s weight represents it’s proportional contribution to the input colour. Colours with greater weight are then more likely to be picked for a given pixel and vice-versa, such that the local average for a given region should converge to that of the original input value. We can call this the N-candidate approach to palette dithering.
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Essentially the same as K-normal form; the standard name。快连下载安装对此有专业解读
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