Vectorize for loop: corr2(A(:,:,i),B(:,:,i))

3 Ansichten (letzte 30 Tage)
William Thielicke
William Thielicke am 3 Dez. 2020
Kommentiert: Bruno Luong am 3 Dez. 2020
Hi, I am trying to accelerate a function and am unable to perform this myself, so I am hoping for your help.
I have a set of 10.000 small images (64x64), and I need to calculate the correlation coefficient for each of these images. This is the code:
clear all
clc
close all
A=rand(64,64,10000);
B=rand(64,64,10000);
corr_result=zeros(1,1,size(A,3));
tic
for i=1:size(A,3)
corr_result(i)=corr2(A(:,:,i),B(:,:,i));
end
toc
I found this, it results in a 64x64x1 matrix, but I need a 1x1x10000 matrix.... Thanks for your input!!
  5 Kommentare
Ameer Hamza
Ameer Hamza am 3 Dez. 2020
I think this is already as efficient as it can get in MATLAB. After JIT optimizations, for-loops are not as slow as one might think.
William Thielicke
William Thielicke am 3 Dez. 2020
But Matlab is only using 50% of my CPU during this operation. I bet there is a faster way...

Melden Sie sich an, um zu kommentieren.

Akzeptierte Antwort

Bruno Luong
Bruno Luong am 3 Dez. 2020
Bearbeitet: Bruno Luong am 3 Dez. 2020
If you have R2020b, you mght try to vectorize with pagemtimes function (or use mtimesx from File exchange)
meanA = mean(A,[1 2]);
meanB = mean(B,[1 2]);
Ac = A-meanA;
Bc = B-meanB;
Ac = reshape(Ac,[],1,size(A,3));
Bc = reshape(Bc,[],1,size(B,3));
% psfun = @(a,b) sum(a.*b,1);
psfun = @(a,b) pagemtimes(a,'transpose',b,'none');
C = psfun(Ac,Bc)./sqrt(psfun(Ac,Ac).*psfun(Bc,Bc))
  3 Kommentare
William Thielicke
William Thielicke am 3 Dez. 2020
... but beware when you hit the limit of your RAM.... then it suddenly becomes 7 times slower. Is there a way to predict which method is faster BEFORE doing the calculation? I guess it has something to do with the memory used by the variables and the available RAM.
Bruno Luong
Bruno Luong am 3 Dez. 2020
Divide the calculation into a chunks that do not exeed your PC ram, eg 8e4 images.

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (0)

Produkte

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by