Efficient Coding to save run time
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I have a three dimensional cell that holds images (i.e. images = cell(10,4,5)) and each cell block holds images of different sizes. The sizes are not too important in terms of what I’m trying to achieve. I would like to know if there is an efficient way to compute the sharpness of each of these cell blocks (total cell blocks = 10*4*5 = 200). I need to compute the sharpness of each block using the following function:
If it matters:
- 40 cell blocks contain images of size 240 X 320
- 40 cell blocks contain images of size 120 X 160
- 40 cell blocks contain images of size 60 X 80
- 40 cell blocks contain images of size 30 X 40
- 40 cell blocks contain images of size 15 X 20
which totals to 200 cells.
%%Sharpness Estimation From Image Gradients
% Estimate sharpness using the gradient magnitude.
% sum of all gradient norms / number of pixels give us the sharpness
% metric.
function [sharpness]=get_sharpness(G)
[Gx, Gy]=gradient(double(G));
S=sqrt(Gx.*Gx+Gy.*Gy);
sharpness=sum(sum(S))./(480*640);
Currently I am doing the following:
sharpness = size(images);
for i = 1 : 10
for j = 1 : 4
for k = 1 : 5
sharpness(i,j,k) = get_sharpness(images{i,j,k});
end
end
end
The sharpness function isn’t anything fancy. I just have a lot of data hence it takes a long time to compute everything.
Currently I am using a nested for loop that iterates through each cell block. Hope someone can help me find a better solution.
(P.S. This is my first time asking a question hence if anything is unclear please ask further questions. THANK YOU)
回答（1 个）
Andrei Bobrov
2016-6-22
sharpness = zeros(size(images));
for ii = 1 : 10
for jj = 1 : 4
for k = 1 : 5
sharpness(ii,jj,k) = get_sharpness(images{ii,jj,k});
end
end
end
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2016-6-22
2016-6-22
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