colfilt

Column-wise neighborhood operations

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Syntax

B = colfilt(A,[m n],block_type,fun)
B = colfilt(A,[m n],[mblock nblock],block_type,fun)
B = colfilt(A,'indexed',___)

Description

B = colfilt(A,[m n],block_type,fun) processes the image A by rearranging each m-by-n block of A into a column of a temporary matrix, and then applying the function fun to this matrix. colfilt zero-pads A, if necessary.

example

B = colfilt(A,[m n],[mblock nblock],block_type,fun) subdivides A into regions of size mblock-by-nblock blocks to save memory. Note that the result of the operation does not change when using the [mblock nblock] argument.

For example, if [mblock nblock] is [3 4] and the size of each block is 16-by-16 pixels, then colfilt subdivides the image into regions of size 48-by-64 pixels and processes each region separately.

B = colfilt(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.

Examples

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Open Live Script

This example shows how to set each output pixel to the mean value of the input pixel's 5-by-5 neighborhood using column-wise neighborhood processing.

Read a grayscale image into the workspace.

I = imread('tire.tif');

Perform column-wise filtering. The function mean is called on each 5-by-5 pixel neighborhood.

I2 = uint8(colfilt(I,[5 5],'sliding',@mean));

Display the original image and the filtered image.

imshow(I)
title('Original Image')

Figure contains an axes object. The hidden axes object with title Original Image contains an object of type image.

figure
imshow(I2)
title('Filtered Image')

Figure contains an axes object. The hidden axes object with title Filtered Image contains an object of type image.

Input Arguments

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Image, specified as an array of any class supported by fun.

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 each block.

Block group size, specified as a 2-element vector of positive integers. mblock is the number of blocks in the group in the vertical direction, and nblock is the number of blocks in the group in the horizontal direction.

Block type, specified as 'sliding' for sliding neighborhoods or 'distinct' for distinct blocks.

Data Types: char | string

Function handle, specified as a handle. The input and output arguments to this function depend on the value of block_type. For more information, see Algorithms.

For more information about function handles, see Create Function Handle.

Output Arguments

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Filtered image, returned as a numeric matrix.

Algorithms

The algorithm that colfilt uses to process images depends on the value of block_type.

Value

Description

'distinct'

  • First, colfilt rearranges each m-by-n block of A into a column in a temporary matrix by using the im2col function.

  • Next, colfilt applies the function fun to this temporary matrix. fun must return a matrix the same size as the temporary matrix.

  • Finally, colfilt rearranges the columns of the matrix returned by fun into m-by-n distinct blocks, by using the col2im function.

'sliding'

  • First, colfilt rearranges each m-by-n neighborhood of A into a column in a temporary matrix by using the im2col function.

  • Next, colfilt applies the function fun to this temporary matrix. fun must return a row vector containing a single value for each column in the temporary matrix. (Column compression functions such as sum return the appropriate type of output.)

  • Finally, colfilt reshapes the vector returned by fun into a matrix the same size as A, by using the reshape function.

To save memory, the colfilt function might divide A into subimages and process one subimage at a time. This implies that fun may be called multiple times, and that the first argument to fun may have a different number of columns each time.

Version History

Introduced before R2006a

See Also

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