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## Hybrid median filtering

version 1.1.0.0 (2.84 KB) by Damien Garcia

### Damien Garcia (view profile)

HMF performs hybrid median filtering of a 2-D array or an RGB image

Updated 25 Feb 2010

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
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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
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% original image
I = ind2rgb(I,map);
% noisy image
J = imnoise(I,'salt & pepper',0.02);
% hybrid median filtering
K = hmf(J,9);
% figures
subplot(121),imshow(J),subplot(122),imshow(K)

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Other examples are given in:
http://www.biomecardio.com/matlab/hmf.html
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### Cite As

Damien Garcia (2020). Hybrid median filtering (https://www.mathworks.com/matlabcentral/fileexchange/25825-hybrid-median-filtering), MATLAB Central File Exchange. Retrieved .

Deepanshu Mehta

SARATH JV

NCC A.

Michael

### Michael (view profile)

A very straight forward and easy to use file. I used this on a disparity image from a pair of stereo cameras with clean results.