nlfilter

General sliding-neighborhood operations

Description

example

B = nlfilter(A,[m n],fun) applies the function fun to each m-by-n sliding block of the grayscale image A.

B = nlfilter(A,'indexed',___) processes A as an indexed image, padding with 0s if the class of A is uint8, uint16, or logical, and padding with 1s otherwise.

Note

nlfilter can take a long time to process large images. In some cases, the colfilt function can perform the same operation much faster.

Examples

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This example shows how to apply a median filter to an image using nlfilter. This example produces the same result as calling medfilt2 with a 3-by-3 neighborhood.

Read an image into the workspace.

Convert the image to double.

A = im2double(A);

Create the function you want to apply to the image—a median filter.

fun = @(x) median(x(:));

Apply the filter to the image.

B = nlfilter(A,[3 3],fun);

Display the original image and the filtered image, side-by-side.

montage({A,B})
title('Original Image (Left) and Median Filtered Image (Right)') Input Arguments

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Image to be filtered, specified as a numeric array of any class supported by 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.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

Block size, specified as a 2-element vector of positive integers. m is the number of rows and n is the number of columns in the block.

Example: B = nlfilter(A,[3 3],fun);

Data Types: single | double | logical

Function handle specified as a handle. The function must accept an m-by-n matrix as input and return a scalar result.

c = fun(x)

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.

Data Types: function_handle

Output Arguments

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Filtered image, returned as numeric array. The class of B depends on the class of the output from fun.