I've been using blockproc
for processing images blockwise. Unfortunately, blockproc
is part of the Image Processing Toolbox, which I don't have on my personal computer.
Is there a combination of functions in base Matlab that can substitute for blockproc
?
My initial guess was to use im2col
to transform each block into columns, and then arrayfun
to process each column. Then I realized that im2col
is also a part of the Image Processing Toolbox, so that doesn't solve my problem.
Here is an example using MAT2CELL. It dividing the image into N-by-M tiles, and handles the case when the image size is not evenly divisible by the number of tiles.
%# 2D grayscale image
I = imread('coins.png');
%# desird number of horizontal/vertical tiles to divide the image into
numBlkH = 4;
numBlkW = 4;
%# compute size of each tile in pixels
[imgH,imgW,~] = size(I);
szBlkH = [repmat(fix(imgH/numBlkH),1,numBlkH-1) imgH-fix(imgH/numBlkH)*(numBlkH-1)];
szBlkW = [repmat(fix(imgW/numBlkW),1,numBlkW-1) imgW-fix(imgW/numBlkW)*(numBlkW-1)];
%# divide into tiles, and linearize using a row-major order
C = mat2cell(I, szBlkH, szBlkW)';
C = C(:);
%# display tiles i subplots
figure, imshow(I)
figure
for i=1:numBlkH*numBlkW
subplot(numBlkH,numBlkW,i), imshow( C{i} )
end
The input image and the resulting tiles:
Won't mat2tiles together with cellfun
and cell2mat
do more or less what blockproc
does?
You could write a wrapper yourself to make it use the same arguments as blockproc
, I don't think it should be that hard to do.
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