Image Processing Toolbox™

colfilt - Columnwise neighborhood operations

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. fun must be a function handle. colfilt zero-pads A, if necessary.

Before calling fun, colfilt calls im2col to create the temporary matrix. After calling fun, colfilt rearranges the columns of the matrix back into m-by-n blocks using col2im.

block_type is a string that can have one of the values listed in this table.

Note   colfilt can perform operations similar to blkproc and nlfilter, but often executes much faster.

B = colfilt(A,[m n],[mblock nblock],block_type,fun) processes the matrix A as above, but in blocks of size mblock-by-nblock to save memory. Note that using the [mblock nblock] argument does not change the result of the operation.

B = colfilt(A,'indexed',...) processes A as an indexed image, padding with 0's if the class of A is uint8 or uint16, or 1's if the class of A is double or single.

Note   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.

Class Support

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.

Examples

Set each output pixel to the mean value of the input pixel's 5-by-5 neighborhood.

I = imread('tire.tif');
imshow(I)
I2 = uint8(colfilt(I,[5 5],'sliding',@mean));
figure, imshow(I2)

See Also

blkproc, col2im, function_handle, im2col, nlfilter

col2im

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