Median filtering with large kernel can be pretty ugly as it gives pixels who are far away the same weight. I prefer weighting them (for example with a gaussian)

Median filtering with large kernel can be pretty ugly as it gives pixels who are far away the same weight. I prefer weighting them (for example with a gaussian) and using a weighted histogram, use the weighted median value (interpolated between two values). It gives a result even more interesting (for some uses) than a simple gaussian blur and you can also configure the weights to make it edge preserving like a bilateral blur but better There is also no way to split up the median computation What does this mean here ? Seems like we could have a rolling window by adding and subtracting pixels on the way. I’ve coded this before, although it’s not O(1) like the algorithm described at the end