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• W1979369422 abstract "Local image histograms contain a great deal of information useful for applications in computer graphics, computer vision and computational photography. Making use of that information has been challenging because of the expense of computing histogram properties over large neighborhoods. Efficient algorithms exist for some specific computations like the bilateral filter, but not others. Here, we present an efficient and practical method for computing accurate derivatives and integrals of locally-weighted histograms over large neighborhoods. The method allows us to compute the location, height, width and integral of all local histogram modes at interactive rates. Among other things, it enables the first constant-time isotropic median filter, robust isotropic image morphology operators, an efficient dominant mode filter and a non-iterative alternative to the mean shift. In addition, we present a method to combat the over-sharpening that is typical of histogram-based edge-preserving smoothing. This post-processing step should make histogram-based filters not only fast and efficient, but also suitable for a variety of new applications." @default.
• W1979369422 created "2016-06-24" @default.
• W1979369422 creator A5006830648 @default.
• W1979369422 creator A5036542947 @default.
• W1979369422 date "2010-07-26" @default.
• W1979369422 modified "2023-09-23" @default.
• W1979369422 title "Smoothed local histogram filters" @default.
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• W1979369422 doi "https://doi.org/10.1145/1778765.1778837" @default.
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