【发布时间】:2012-03-04 15:41:12
【问题描述】:
我编写了一个 matlab 函数,它对图像执行一些 cpu 密集型操作。我想提高这个功能的速度,但想不出优化它的方法。有谁知道如何进一步优化下面的功能?
function imageMedoid(imageList, resizeFolder, outputFolder, x, y)
% local variables
medoidImage = zeros([1, y*x, 3]);
alphaImage = zeros([y x]);
medoidContainer = zeros([y*x, length(imageList), 3]);
% loop through all images in the resizeFolder
for i=1:length(imageList)
% get filename and load image
fname = imageList(i).name;
container = im2double(imread([resizeFolder fname]));
% load alpha channel, convert to zeros and ones, add to alphaImage
[~,~,alpha] = imread([resizeFolder fname]);
alpha = double(alpha) / 255;
alphaImage = alphaImage + alpha;
% add (r,g,b) values to medoidContainer and reshape to single line
medoidContainer(:, i, :) = reshape(container, [y*x 3]);
end
% loop through every pixel in medoidContainer
for i=1:length(medoidContainer)
% calculate distances between all values for current pixel
distances = pdist(squeeze(medoidContainer(i,:,1:3)));
% convert found distances to matrix of distances
distanceMatrix = squareform(distances);
% find index of image with the medoid value
[~, j] = min(mean(distanceMatrix,2));
% write found medoid value to medoidImage
medoidImage(1, i, 1:3) = medoidContainer(i, j, 1:3);
end
% replace values larger than one in alpha channel
alphaImage(alphaImage > 1) = 1;
% reshape image to original proportions
medoidImage = reshape(medoidImage, y, x, 3);
% save medoid image
imwrite(medoidImage, [outputFolder 'medoid.png'], 'Alpha', alphaImage);
任何建议将不胜感激!
【问题讨论】:
标签: matlab optimization