The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:
After hooking any function, I immediately called mockToString on it. From that point on, if fermaw’s integrity check asked .toString() whether appendBuffer was native, it would receive the pristine, authentic-looking answer: function appendBuffer() { [native code] }. Basically, it’s like asking your ex if they cheated on you and they did but they say they didn’t and you take their word for it because reasons. Don’t worry, on écoute et on ne juge pas.
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