Hybrid median filtering 1.0

B = HMF(A,N) performs hybrid median filtering of the matrix A using a NxN box. Hybrid median filtering preserves edges better than a NxN square kernel-based median filter because data from different spatial directions are ranked separately. Three median values are calculated in the NxN box: MR is the median of horizontal and vertical R pixels, and MD is the median of diagonal D pixels. The filtered value is the median of the two median values and the central pixel C: median([MR,MD,C]).B = HMF(A) uses N = 5 (default value).A can be a 2-D array or an RGB image. If A is an RGB image, hybrid median filtering is performed in the HSV color space. Notes------1) N must be odd. If N is even then N is incremented by 1.2) The Image Processing Toolbox is required.3) If the function NANMEDIAN exists (Statistics Toolbox), NaNs are treated as missing values and are ignored. Example--------% original image[I,map] = imread('trees.tif');I = ind2rgb(I,map);% noisy imageJ = imnoise(I,'salt & pepper',0.02);% hybrid median filteringK = hmf(J,9);% figuressubplot(121),imshow(J),subplot(122),imshow(K)------Other examples are given in:http://www.biomecardio.com/matlab/hmf.html-----

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Array,  Exists,  Function,  Image,  Incremented,  Nanmedian,  Processing,  Required,  Toolbox
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