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Sliding neighborhood - how to vectorize?

조회 수: 2 (최근 30일)
Alex Kurek
Alex Kurek 2015년 9월 25일
편집: Joseph Cheng 2015년 10월 2일
Dear all,
Can you please help me to vectorize (or speed-up somehow else) this code? Below is the original (parfor) version and the vectorized one, but its not working (the image is different). How to vectorize this, where is the error? The inner loop (two lines) is executed 47 bln times in my code, so any speed up is a good thing.
noised = imnoise(zeros(230,230), 'salt & pepper', 0.2);
imshow(noised, []); impixelinfo
%%Oryginal
myTempModel = zeros(1, 230);
signalInBlock = zeros(230, 230);
tic
parfor i = 1 : 199
myTemp = myTempModel;
ii=i+31;
for j = 1 : 199
block = noised( i:ii, j:j+31);
myTemp(j+15) = sum(block(:));
end
signalInBlock(i+15, :) = myTemp;
end
toc
imshow(signalInBlock,[]); impixelinfo
%%Vectorized, but not working
signalInBlock = zeros(230, 230);
tic
i = 1:1:199;
j = 1:1:199;
signalInBlock(i+15, j+15) = sum(sum(noised(i:i+31, j:j+31)));
toc
imshow(signalInBlock,[]); impixelinfo
Best regards, Alex

채택된 답변

Joseph Cheng
Joseph Cheng 2015년 9월 25일
why not use conv2?
signalInBlock2 = zeros(230, 230);
tic
temp = conv2(noised,ones(32,32),'valid');
signalInBlock2(16:214,16:214)=temp;
figure,imshow(signalInBlock2,[]);
toc
when running your code the parfor took 0.327807 seconds, the conv2 took 0.131374 seconds
  댓글 수: 3
Alex Kurek
Alex Kurek 2015년 9월 30일
편집: Alex Kurek 2015년 9월 30일
I tried this:
noiseFrameCollector = zeros(230, 230, 30);
signalInBlock = noiseFrameCollector;
zzz = 1:1:30;
tic
signalInBlock(:,:,zzz) = squaredFrameProcess(noiseFrameCollector(:,:,zzz), signalInBlock);
toc
But got the following error:
Undefined function 'conv2' for input arguments of type 'double' and attributes 'full 3d real'. Error in squaredFrameProcess (line 3) temp = conv2(noised, arrayOnes, 'valid');
Is there any other possibility?
Joseph Cheng
Joseph Cheng 2015년 10월 2일
편집: Joseph Cheng 2015년 10월 2일
for that conv2 is for a 2D matrix if my memory of the documentation is correct. you can write a for loop to go through each "layer" of signalblock. which if large the parallel tool box can make if faster if it is really slow since each "layer" is not dependent on each other. As for GPU processing, i'm still dabbling in using the GPU so i'm not sure.

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추가 답변 (1개)

Alex Kurek
Alex Kurek 2015년 9월 25일
Thank you,
I implemented it like this (toc after figure, preallocation):
signalInBlock2 = zeros(230, 230);
tic
arrayOnes = ones(32,32);
temp = conv2(noised, arrayOnes, 'valid');
signalInBlock2(16:214, 16:214) = temp;
toc
figure, imshow(signalInBlock2, []);
And it takes 0.005525 seconds with is 34x faster.
Now I wonder if there is something faster than conv2
  댓글 수: 2
Joseph Cheng
Joseph Cheng 2015년 9월 25일
편집: Joseph Cheng 2015년 9월 25일
good catch, I stuck the figure portion towards the end to visually compare the parfor output and the conv2 output. forgot to copy the timing results without the figure when replying to you
Image Analyst
Image Analyst 2015년 9월 25일
conv2() is highly optimized, especially for separable kernels like you're using (just a flat box filter). You won't find anything faster. You could compare it with imfilter() if you want - it's similar.

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