Larger size matrix comparison faster elementwise

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ashwin sharma
ashwin sharma 2017-7-4
评论： Jan 2017-7-5
I want to find the equal elements in two matrices, but size is larger so for loop taking too much time. please suggest how to increase speed.
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ashwin sharma
ashwin sharma 2017-7-5
number of equal elements divided by the number of all elements
Image Analyst
Image Analyst 2017-7-5
But how do you compare them when they are not the same size? There are ways but you need to tell us. Or do you just want to compare the pairs that are the same size with each other, and not to the different sized ones, like
percentSimilar = sum(sum(m1 == m2)) / numel(m1);

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回答（3 个）

Guillaume
Guillaume 2017-7-4
Elementwise comparison has never needed a loop:
A == B
is all that is needed. And if you want the values at the position where they're equal:
A(A == B)
Unless you're talking about another sort of equality (e.g. intersect, which also wouldn't need a loop)
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Jan
Jan 2017-7-5
@Guillaume: The magic moment of trailing zeros has gone. Walter has been a little bit too slow - I did not think I'd ever say that. Now please restart to answer questions ;-)

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Image Analyst
Image Analyst 2017-7-4
You only need to shift the 36*79820 matrix 180 by 180 within the larger 36*80000 matrix to check matches or other things at each shift location. That's only 14,400 loop iterations - very small and fast. You can compare in a variety of ways, such as psnr(), isequal(), ssim(), normxcorr2(), etc.
Guillaume
Guillaume 2017-7-5
Still not entirely sure what you call similar, particularly with matrices of different size. If you want the number of elements that are common between the two matrices regardless of location, then as said you can use intersect:
numcommonelements = numel(intersect(matrix1(:), matrix2(:)))
However the above will ignore duplicated elements. If you have duplicated elements, two calls to ismember would do:
numcommonin1 = sum(ismember(matrix1(:), matrix2(:)));
numcommonin2 = sum(ismember(matrix2(:), matrix1(:)));

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