Vectorize a per-pixel classification
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Hi, I am using the following code to calculate the likelihood of every pixel x in a RGB image, belonging to a given class;
for count=1:height
for count2=1:width
%pixel vector x to be classified
x=[image(count,count2,1);image(count,count2,2);image(count,count2,3)];
%for each class
for count3=1:noOfClasses
detZ = pDet(count3);
invZ = pInv(:,:,count3);
y=(pMean(count3,:)');
%calculate the likelihood
post= 1/sqrt((2*pi)^2*detZ) * exp(-(x(:,1)-y)'*invZ*(x(:,1)-y)/2);
......
The application is classification of video frames and so the current approach using for loops is impractical as it is very slow.
Any suggestions?
thanks, John
采纳的回答
Teja Muppirala
2011-4-12
The key is recognizing that:
diag(R*A*R') == sum(R*A.*R,2);
Try the following code. It does exactly what your code does, using only one loop, and runs 100 times faster.
clc
I = imread('peppers.png'); I = double(I)/255;
[height,width,~] = size(I);
image = I;
noOfClasses = 5;
pDet = rand(noOfClasses,1);
pInv = rand(3,3,noOfClasses);
pMean = rand(noOfClasses,3);
% ----------------------The original way----------------------
disp('First do it the original way...')
tic
post(height,width,noOfClasses) = 0;
for count=1:height
for count2=1:width
%pixel vector x to be classified
x=[image(count,count2,1);image(count,count2,2);image(count,count2,3)];
%for each class
for count3=1:noOfClasses
detZ = pDet(count3);
invZ = pInv(:,:,count3);
y=(pMean(count3,:)');
%calculate the likelihood
post(count,count2,count3)= 1/sqrt((2*pi)^2*detZ) * exp(-(x(:,1)-y)'*invZ*(x(:,1)-y)/2);
end
end
end
originalway = toc
% ----------------------The fast way----------------------
disp('Now do it the fast way...')
RGB = reshape(I,[],3);
%[colorlist, ~, ind] = unique(RGB,'rows');
colorlist = RGB;
C = 1./sqrt((2*pi)^2*pDet);
ncol = size(colorlist,1);
tic
post2(height,width,noOfClasses) = 0;
for count3=1:noOfClasses
invZ = pInv(:,:,count3);
y=(pMean(count3,:)');
colorlistY = bsxfun(@minus,colorlist,y');
post2(:,:,count3) = reshape(C(count3) * exp(-sum(colorlistY*invZ.*colorlistY,2)/2) , height, width);
end
fasterway = toc
ARETHEYTHESAME = isequal(post,post2)
2 个评论
Teja Muppirala
2011-4-12
Yikes... please don't take after my sloppy code. This:
post(height,width,noOfClasses) = 0;
is really a lot safer when written as:
post = zeros(height,width,noOfClasses);
John
2011-5-19
更多回答（1 个）
Jan
2011-4-12
Move as many operations as possible out of the loops:
C1 = 1 ./ sqrt((2*pi)^2 * pDet);
pMeanT = transpose(pMean);
for count=1:height
for count2=1:width
x = reshape(image(count, count2, :), 3, 1);
for count3=1:noOfClasses
invZ = pInv(:,:,count3);
y = pMeanT(:, count3);
C2 = x - y;
post = C1(count3) * exp(-C2' * invZ * C2 * 0.5);
I do not expect a dramatic acceleration, but this is a very general method which works in all programming languages.
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