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Hybrid median filtering

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Hybrid median filtering

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12 Nov 2009 (Updated )

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

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Description

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
--------
% original image
[I,map] = imread('trees.tif');
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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Required Products Image Processing Toolbox
MATLAB release MATLAB 7.5 (R2007b)
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Comments and Ratings (2)
10 Oct 2012 NCC A.  
03 Feb 2010 Michael

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.

Updates
25 Feb 2010

Test for RGB has been improved. RGB output and input have same class.

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