一种方法是使用accumarray.不幸的是，为了做到这一点，我们首先需要标记"您的逻辑矩阵.如果您没有图像处理工具箱，这是一种复杂的操作方式:

One approach is to use accumarray. Unfortunately in order to do that we first need to "label" your logical matrix. Here is a convoluted way of doing that if you don't have the image processing toolbox:

sz=size(myLogicals);
s_ind(sz(1),sz(2))=0;
%// OR: s_ind = zeros(size(myLogicals))

s_ind(starts) = 1;
labelled = cumsum(s_ind(:)).*myLogicals(:);        

所以Shai的bwlabeln实现就是这样做的(但是形状是1 -by- numel(myLogicals)，而不是形状的size(myLogicals))

So that just does what Shai's bwlabeln implementation does (but this will be 1-by-numel(myLogicals) in shape as opposed to size(myLogicals) in shape)

现在您可以使用accumarray:

accumarray(labelled(myLogicals), myArray(myLogicals), [], @max)

否则尝试起来可能会更快

or else it may be faster to try

result = accumarray(labelled+1, myArray(:), [], @max);
result = result(2:end)

这是完全矢量化的，但是值得吗?您必须针对您的循环解决方案进行速度测试才能知道.

This is fully vectorized, but is it worth it? You'll have to do speed tests against your loop solution to know.