Kirsch边缘检测算子MATLAB怎么调用

I = imread('Lena.bmp');
imshow(I),title('原图');

BW5 = edge(I,'kirsch');
figure;
imshow(BW5,[]),title('kirsch算子边缘检测');
程序如上，直接调用就可以

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%读出要处理的图象
clear
clc
close all
bw=imread('e:\11.jpg');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%对图象进行预处理

%画出原始图象
bw1=rgb2gray(bw);
figure(1)
imshow(bw1)
title('原始图象')

%对图象进行均值滤波处理
bw2=filter2(fspecial('average',3),bw1);
figure(2)
imshow(bw2)
title('均值滤波')

%对图象进行高斯滤波处理
bw3=filter2(fspecial('gaussian'),bw2);
figure(3)
imshow(bw3)
title('高斯滤波')

%利用小波变换对图象进行降噪处理
[thr,sorh,keepapp]=ddencmp('den','wv',bw3); %获得除噪的缺省参数
bw4=wdencmp('gbl',bw3,'sym4',2,thr,sorh,keepapp);%图象进行降噪处理
figure(4)
imshow(bw4)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%提取图象边缘
t=1200 ; %设定阈值
colormap(gray(256)); %设定调色板
bw5=double(bw4); %把图变为十进制数
[m,n]=size(bw5); %得到图像的大小（长和宽）
g=zeros(m,n); %定义一个大小为S的零矩阵
%利用Sobel算子进行边缘提取
for i=2:m-1
for j=2:n-1
d1 =(5*bw5(i-1,j-1)+5*bw5(i-1,j)+5*bw5(i-1,j+1)-3*bw5(i,j-1)-3*bw5(i,j+1)-3*bw5(i+1,j-1)-3*bw5(i+1,j)-3*bw5(i+1,j+1))^2; %Sobel算子的dx(垂直梯度)
d2 =((-3)*bw5(i-1,j-1)+5*bw5(i-1,j)+5*bw5(i-1,j+1)-3*bw5(i,j-1)+5*bw5(i,j+1)-3*bw5(i+1,j-1)-3*bw5(i+1,j)-3*bw5(i+1,j+1))^2; %Sobel算子的dy(水平梯度)
d3 =((-3)*bw5(i-1,j-1)-3*bw5(i-1,j)+5*bw5(i-1,j+1)-3*bw5(i,j-1)+5*bw5(i,j+1)-3*bw5(i+1,j-1)-3*bw5(i+1,j)+5*bw5(i+1,j+1))^2;
d4 =((-3)*bw5(i-1,j-1)-3*bw5(i-1,j)-3*bw5(i-1,j+1)-3*bw5(i,j-1)+5*bw5(i,j+1)-3*bw5(i+1,j-1)+5*bw5(i+1,j)+5*bw5(i+1,j+1))^2;
d5 =((-3)*bw5(i-1,j-1)-3*bw5(i-1,j)-3*bw5(i-1,j+1)-3*bw5(i,j-1)-3*bw5(i,j+1)+5*bw5(i+1,j-1)+5*bw5(i+1,j)+5*bw5(i+1,j+1))^2;
d6 =((-3)*bw5(i-1,j-1)-3*bw5(i-1,j)-3*bw5(i-1,j+1)+5*bw5(i,j-1)-3*bw5(i,j+1)+5*bw5(i+1,j-1)+5*bw5(i+1,j)-3*bw5(i+1,j+1))^2;
d7 =(5*bw5(i-1,j-1)-3*bw5(i-1,j)-3*bw5(i-1,j+1)+5*bw5(i,j-1)-3*bw5(i,j+1)+5*bw5(i+1,j-1)-3*bw5(i+1,j)-3*bw5(i+1,j+1))^2;
d8 =(5*bw5(i-1,j-1)+5*bw5(i-1,j)-3*bw5(i-1,j+1)+5*bw5(i,j-1)-3*bw5(i,j+1)-3*bw5(i+1,j-1)-3*bw5(i+1,j)-3*bw5(i+1,j+1))^2;

g(i,j)=round(sqrt(d1+d2+d3+d4+d5+d6+d7+d8)); %梯度模取整
end
end
for i=1:m
for j=1:n
if g(i,j)>t
bw5(i,j)=255; %将梯度值与阈值比较 ，大于T则把图像的灰度变为255，小于T则把图像的灰度变为0
else
bw5(i,j)=0;
end
end
end
%显示边缘提取后的图象
figure(5)
imshow(bw5)
title('kirsch边缘检测')