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B = nlfilter(A, [m n], fun)
B = nlfilter(A, 'indexed',...)
B = nlfilter(A, [m n], fun) applies the function fun to each m-by-n sliding block of the grayscale image A. fun is a function that accepts an m-by-n matrix as input and returns a scalar result.
c = fun(x)
fun must be a function handle.
Parameterizing Functions, in the MATLAB Mathematics documentation, explains how to provide additional parameters to the function fun.
c is the output value for the center pixel in the m-by-n block x. nlfilter calls fun for each pixel in A. nlfilter zero-pads the m-by-n block at the edges, if necessary.
B = nlfilter(A, 'indexed',...) processes A as an indexed image, padding with 1's if A is of class single or double and 0's if A is of class logical, uint8, or uint16.
The input image A can be of any class supported by fun. The class of B depends on the class of the output from fun. When A is grayscale, it can be any numeric type or logical. When A is indexed, it can be logical, uint8, uint16, single, or double.
nlfilter can take a long time to process large images. In some cases, the colfilt function can perform the same operation much faster.
This example produces the same result as calling medfilt2 with a 3-by-3 neighborhood.
A = imread('cameraman.tif');
fun = @(x) median(x(:));
B = nlfilter(A,[3 3],fun);
imshow(A), figure, imshow(B)blockproc | colfilt | function_handle

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