clc;close all;clear all
%---------------------------------------------生成高斯平滑滤波模板-------------------------------------------------------------%
hg=zeros(3,3); %设定高斯平滑滤波模板的大小为3*3
delta=0.5;
for x=1:1:3
for y=1:1:3
u=x-2;
v=y-2;
hg(x,y)=exp(-(u^2+v^2)/(2*pi*delta^2));
end
end
h=hg/sum(hg(:));
%------------------------------------------------读入图像------------------------------------------------------------------------%
f = imread('F:\ZPB\3.tif'); % 读入图像文件
f=rgb2gray(im2double(f));
imshow(f)
title('原始图像');
[m,n]=size(f);
ftemp=zeros(m,n);
rowhigh=m-1;
colhigh=n-1;
%%%---------------------------------------------高斯滤波----------------------------------------%%%
for x=2:1:rowhigh-1
for y=2:1:colhigh-1
mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1); f(x,y-1) f(x,y) f(x,y+1);f(x+1,y-1) f(x+1,y) f(x+1,y+1)];
A=h.*mod;
ftemp(x,y)=sum(A(:));
end
end
f=ftemp
figure,imshow(f)
title('通过高斯滤波器后的图像');
%----------------------------------------利用roberts算子进行边缘检测--------------------------------------------------%
sx=[-1 -2 -1;0 0 0;1 2 1];
sy=[-1 0 1;-2 0 2;-1 0 1];%%%%%你可以替换成其他算子，这里是罗伯特算子
% sx=[-1 -2 -1;0 0 0;1 2 1];
% sy=[-1 0 1;-2 0 2;-1 0 1];这个是Sobel算子，类似的，你可以替换成canny算子等等
for x=2:1:rowhigh-1
for y=2:1:colhigh-1
mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1); f(x,y-1) f(x,y) f(x,y+1);f(x+1,y-1) f(x+1,y) f(x+1,y+1)];
fsx=sx.*mod;
fsy=sy.*mod;
ftemp(x,y)=sqrt((sum(fsx(:)))^2+(sum(fsy(:)))^2);
end
end
fr=im2uint8(ftemp);
figure,imshow(fr)
title('用roberts算子边缘检测的原始图像');
%--------------------------------------域值分割，这部分可不参---------------------------------------------------------------%
TH1=60; %设定阈值
for x=2:1:rowhigh-1
for y=2:1:colhigh-1
if (fr(x,y)>=TH1)&((fr(x,y-1) <= fr(x,y)) & (fr(x,y) > fr(x,y+1)) )
fr(x,y)=200;
elseif(fr(x,y)>=TH1)&( (fr(x-1,y) <=fr(x,y)) & (fr(x,y) >fr(x+1,y)))
fr(x,y)=200;
else fr(x,y)=50;
end
end
end
figure,imshow(fr)
title('用roberts算子边缘检测并细化后的图像');
