How to speed up column wise operation in MATLAB using bsxfun?

Question

I am trying to calculate the Square Euclidean Distance between each column from two matrices and store in matrix D.

im_patches is 81*60840 double

codebook is 81*456 double

SquareEuclidean = @(x, y) x'*x+y'*y-2*x'*y;

% Get N*K distance matrix D between the N patches extracted
% from the image (im patches) and the K prototypes in the codebook
D=zeros(size(im_patches,2),size(codebook, 2));

for i=1:size(im_patches,2)
    for j=1:size(codebook, 2)
        D(i,j)=SquareEuclidean(im_patches(:,i),codebook(:,j));
    end
end

However, this is very inefficient that cost more than 10 minutes in my laptop.

I am wondering is there a better way of using bsxfun. So I tried:

D2 = bsxfun(@(x,y) x'.*x+y'.*y-2.*x'.*y,im_patches,codebook);

which gives an error:

Error using bsxfun: Non-singleton dimensions of the two input arrays must match each other.

I think bsxfun or arrayfun would be a nice way of dealing such problem. But don't know the correct way of doing this.

Thank you in advance.

Take a look on [`pdist2`](http://www.mathworks.com/help/stats/pdist2.html) — EBH, Jun 11 '17 at 20:21
@EBH Thank you for your editing and comments, I will check it out. It seems like a nice solution. :) — Kevin, Jun 12 '17 at 12:50

score 1 · Accepted Answer · answered Jun 11 '17 at 20:24

1

Your loop can be reduced to:

bsxfun(@plus,sum(im_patches.'.^2,2),sum(codebook.^2)-2*im_patches.'*codebook)

In MATLAB r2016b there is no need to bsxfun:

sum(im_patches.'.^2,2)+sum(codebook.^2)-2*im_patches.'*codebook

answered Jun 11 '17 at 20:24

rahnema1

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How to speed up column wise operation in MATLAB using bsxfun?

1 Answers1