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.
"What we have found is certain weeks during the year there'll be a hundred bats in here, and then suddenly they will disappear," says Parker.
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siftDown(arr, i, 0); // 对剩余i个元素重新建堆
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