Vectorize'for'循环调用其他函数

Question

我在matlab中有以下代码片段，其中有两个＆＃39; for＆＃39;循环： ＆＃39;我＆＃39;是一个已预先分配的二进制图像。

 ...
    [x,y] = find(bwmorph(I,'endpoints'));
    n=numel(x);
    m=numel(x)-1;
    n=m+1;
    r=i+1;
    for i= 1:m
        for j = r:n
            I=linept(I, x(i), y(i), x(j), y(j));
        end;
    end;
    ...

linept函数如下所示。来自Matlab文件交换：

function result=linept(matrix, X1, Y1, X2, Y2)
result = matrix;
a=max(1, X1);b=sign(X2 - X1);c=max(1, X2);
for x=a:b:c
    y = round(f(x, X1, Y1, X2, Y2));
    if y > 0
        result(x, y) = 1;
    end
end
d=max(1, Y1);e=sign(Y2 - Y1);g=max(1, Y2);
for y=d:e:g
    x = round(f2(y, X1, Y1, X2, Y2));
    if x > 0
        result(x, y) = 1;
    end
end

function y=f(x, X1, Y1, X2, Y2)
a = (Y2 - Y1)/(X2 - X1);
b = Y1 - X1 * a;
y = a * x + b;

function x=f2(y, X1, Y1, X2, Y2)
if X1==X2
    x = X1;
else
    a = (Y2 - Y1)/(X2 - X1);
    b = Y1 - X1 * a;
    x = (y - b)/a;
end

由于许多＆＃39; for＆＃39;循环和函数调用，这个代码运行得非常慢。对于一个端点很少的简单图像，它运行速度很快，但是当边数更多时需要花费很多时间。如果图像的大小是我试图对它进行矢量化并预先分配了一些变量，但是没有太大的改进。任何人都可以帮我解决如何在循环中调用函数的代码。感谢你

Answer 1

这是一个很大的问题!!

简要讨论和解决方案代码

嗯，接下来列出的是一种矢量化方法，它在各个地方大量使用 bsxfun 来照顾expansions所有其他点的连接点，这基本上是怎样的bsxfun运作。其中的代码使用示例输入数据进行演示。看看 -

%// Create demo input data
img = false(20);
img(2,5:15) = 1;
img(12,5:15) = 1;
figure,imagesc(img), colormap gray, title('Starting Binary image')

%// Find endpoints
[X,Y] = find(bwmorph(img,'endpoints'));

%// Make a new binary image with only endpoints in it
I = false(size(img));
I(sub2ind(size(I),X,Y)) = 1;
figure,imagesc(I), colormap gray, title('Endpoints detected')

%-------- Vectorized code starts here ...
[nrows,ncols] = size(I);  %// Parameters
npts = numel(X);

twopts = nchoosek(1:npts,2);
slopes = (Y(twopts(:,1)) - Y(twopts(:,2)))./(X(twopts(:,1)) - X(twopts(:,2)));

%// Find the connecting indices with X-Y as they are, to work with 
%// slopes within [-1 1]
stage1 = abs(slopes)<=1;
[colID,rowID] = connecting_idx(X,Y,twopts(stage1,:),slopes(stage1));
valid = colID>0 & rowID>0 & colID<=ncols & rowID<=nrows;
I((colID(valid)-1)*nrows + rowID(valid))=1;

%// Find the connecting indices with X-Y interchanged, to work with 
%// slopes outside [-1 1]
[rowID,colID] = connecting_idx(Y,X,twopts(~stage1,:),1./slopes(~stage1));
valid = colID>0 & rowID>0 & colID<=ncols & rowID<=nrows;
I((colID(valid)-1)*nrows + rowID(valid))=1;
figure,imagesc(I),colormap gray,title('Final output : Endpoints connected')

相关功能代码（代码库最重要的部分） -

function [y_all,x_all] = connecting_idx(X,Y,twopts,slopes)

%// Find XY indices that connects the X, Y anchor points given the two points
%// combinations and the corresponding slopes

X_twopts = reshape(X(twopts),size(twopts));
Y_twopts = reshape(Y(twopts),size(twopts));

[sortedX_pairs1,sorted_idx1] = sort(X_twopts,2);
X_starts1 = sortedX_pairs1(:,1);
Y_pairs = Y_twopts;
Y_starts = Y_pairs(sorted_idx1==1);
offsets = Y_starts - slopes.*X_starts1;
max_X_len = max(diff(sortedX_pairs1,[],2));

x_all = bsxfun(@plus,X_starts1,[0:max_X_len]);
x_lens = diff(sortedX_pairs1,[],2);
mask = bsxfun(@gt,x_lens+1,0:max_X_len);
y_all = round(bsxfun(@plus,bsxfun(@times,x_all,slopes),offsets));

y_all = y_all(mask);
x_all = x_all(mask);

return;

代码运行后调试图像 -