matlab练习程序（Marr-Hildreth边缘检测）

clear all;
close all;
clc;

%产生LoG算子(Laplacian of Gaussian)
m=11;
n=11;
sigma=1.4;
w=zeros(m,n);
h_m=(m-1)/2;
h_n=(n-1)/2;
for i=1:m
for j=1:n
y=i-h_m;
x=j-h_n;
w(i,j)=(1/(sigma*sigma))*((y*y+x*x)/(sigma*sigma)-2)*exp(-(y*y+x*x)/(2*sigma*sigma));
end
end
w=w/sum(sum(w));    %归一化

img=double(imread('lena.jpg'));
imgn=imfilter(img,w,'replicate');

%过零点检测，一个函数最大值大于零，最小值小于零，那么函数中间一定有为零的点
%准确的过零点的值需要插值
[m n]=size(img);
for i=2:m-1
for j=2:n-1
tmp(1)=sum(sum(imgn(i-1:i,j-1:j)));
tmp(2)=sum(sum(imgn(i-1:i,j:j+1)));
tmp(3)=sum(sum(imgn(i:i+1,j-1:j)));
tmp(4)=sum(sum(imgn(i:i+1,j:j+1)));
Ma=max(tmp);
Mi=min(tmp);
if Ma>0 && Mi<0
imgn(i,j)=255;
end
end
end

imshow(imgn==255);