Question

我正在根据图像中像素的强度差异构建邻接列表。 Matlab中的代码片段如下：

m=1;
len = size(cur_label, 1);
for j=1:len
    for k=1:len
        if(k~=j)    % avoiding diagonal elements
            intensity_diff = abs(indx_intensity(j)-indx_intensity(k));     %intensity defference of two pixels.

            if intensity_diff<=10     % difference thresholded by 10
                adj_list(m, 1) = j;   % storing the vertices of the edge
                adj_list(m, 2) = k;
                m = m+1;
            end
        end
    end
end
y = sparse(adj_list(:,1),adj_list(:,2),1);       % creating a sparse matrix from the adjacency list

如何避免这些讨厌的嵌套for循环？如果图像尺寸很大，那么它的工作就像灾难一样。如果有人有任何解决方案，那对我来说将是一个很大的帮助。问候拉特纳

Answer 1

我假设输入indx_intensity为1D数组。有了这个假设，这是一个带broadcasting/bsxfun -

的矢量化方法

%// Threshold parameter
thresh = 10;

%// Get elementwise differentiation between elements in indx_intensity
diffs = abs(bsxfun(@minus,indx_intensity(:),indx_intensity(:).')) %//'

%// Threshold the differentiations against the threshold, thus giving us a 
%// 2D square matrix. Then, set the diagonal elements to zero to avoid them.
mask = diffs <= thresh;
mask(1:len+1:end) = 0;

%// Get the indices of the TRUE elements in the valid mask as final output.
[R,C] = find(mask);
adj_list_out = [C R];

如何避免在matlab中嵌套for循环？

1 个答案: