【问题标题】:fast computation of histogram on a grid快速计算网格上的直方图
【发布时间】:2011-08-15 20:18:39
【问题描述】:
我有一张 200x200 的灰度图像,我想计算图像中每个 8x8 窗口的强度直方图。我怎样才能计算得那么快?我现在使用 for 循环,但它太慢了。我当前的代码如下所示:
I = imread('image.jpg');
for i=1:8:height-7
for j=1:8:width-7
patch = I(i:i+7,j:j+7);
% compute histogram for the patch
end
end
【问题讨论】:
标签:
matlab
grid
histogram
【解决方案1】:
如果您有图像处理工具箱,您可以使用函数blockproc,这是您的循环的编译和通用版本。只需将回调函数定义为您的直方图计算即可。
B = blockproc(I, [8 8], @myhistfun)
【解决方案2】:
我认为下面的代码可能会回答您的问题。诀窍是不要在循环内调用任何函数并预先分配所有数组。参见例如http://www.quantiphile.com/2010/10/16/optimizing-matlab-code/ 了解更多关于循环加速的信息。无论如何,在我的机器上,加速循环速度要快 17 倍。
% image size
height = 800;
width = 1200;
window = 8;
% histogram bin centers
bin_centers = 0.05:0.1:1;
% here a random image as input
img = rand(height, width);
% verion using accelerated loops (for this to work there cannot be any
% function calls to not built-in functions)
tic
img3 = zeros(window^2, height*width/window^2);
ind = 1;
for i=1:window:height
for j=1:window:width
patch_ = img(i:i+window-1,j:j+window-1);
img3(:,ind) = patch_(:);
ind = ind + 1;
end
end
hist_img3 = hist(img3, bin_centers);
toc
% probably version of user499372 calling hist function within the loop
tic
hist_img4 = zeros(size(hist_img3));
ind = 1;
for i=1:window:height
for j=1:window:width
patch_ = img(i:i+window-1,j:j+window-1);
hist_img4(:,ind) = hist(patch_(:), bin_centers);
ind = ind + 1;
% compute histogram for the patch
end
end
toc
% test the results
all(all(hist_img3==hist_img4))