数字图像处理第四章_冈萨雷斯_gonzales_数字图像处理_源码

%% 空域图像平滑 邻域平均处理 不同窗口的效果 clear all close all if 1==2 %不同窗口的邻域平均处理 I0=imread('lena_gray_256.tif'); [m,n]=size(I0); I=imnoise(I0,'gaussian',0,0.01); ws=3; % 窗口大小 w=double(ones(ws)./(ws*ws)); I3=uint8(filter2(w,I)); ws=5; % 窗口大小 w=double(ones(ws)./(ws*ws)); I5=uint8(filter2(w,I)); ws=7; % 窗口大小 w=double(ones(ws)./(ws*ws)); I7=uint8(filter2(w,I)); subplot('Position',[0,0.5,0.5,0.5]);imshow(I); subplot('Position',[0.5,0.5,0.5,0.5]);imshow(I3); subplot('Position',[0,0,0.5,0.5]);imshow(I5); subplot('Position',[0.5,0,0.5,0.5]);imshow(I7); end %不同窗口的邻域平均处理 %% 生成高斯加权模板 进行平滑滤波 if 1==2 %高斯加权模板平滑滤波 I0=imread('lena_gray_256.tif'); [m,n]=size(I0); I=imnoise(I0,'gaussian',0,0.01); ws=3; % 窗口大小 xigm=2; % 高斯方差 反差为1 ws2=(ws-1)/2; for x=-ws2:ws2 for y=-ws2:ws2 w(x+ws2+1,y+ws2+1)=(exp(-(double(x*x)+double(y*y))/(xigm*xigm)))/(xigm*pi); end end w=w./sum(w(:)); %归一化 Ig3=uint8(filter2(w,I)); ws=5; % 窗口大小 xigm=2; % 高斯方差 反差为1 ws2=(ws-1)/2; for x=-ws2:ws2 for y=-ws2:ws2 w(x+ws2+1,y+ws2+1)=(exp(-(double(x*x)+double(y*y))/(xigm*xigm)))/(xigm*pi); end end w=w./sum(w(:)); %归一化 Ig5=uint8(filter2(w,I)); ws=7; % 窗口大小 xigm=2; % 高斯方差 反差为1 ws2=(ws-1)/2; for x=-ws2:ws2 for y=-ws2:ws2 w(x+ws2+1,y+ws2+1)=(exp(-(double(x*x)+double(y*y))/(xigm*xigm)))/(xigm*pi); end end w=w./sum(w(:)); %归一化 Ig7=uint8(filter2(w,I)); subplot('Position',[0,0.5,0.5,0.5]);imshow(I); subplot('Position',[0.5,0.5,0.5,0.5]);imshow(Ig3); subplot('Position',[0,0,0.5,0.5]);imshow(Ig5); subplot('Position',[0.5,0,0.5,0.5]);imshow(Ig7); end %高斯加权模板平滑滤波 %% 中值滤波 if 1==2 %中值滤波 I0=imread('lena_gray_256.tif'); [m,n]=size(I0); I=imnoise(I0,'gaussian',0,0.01); J=imnoise(I0,'salt & pepper',0.02); ws=3; % 窗口大小 w=double(ones(ws)./(ws*ws)); Iav=uint8(filter2(w,I)); Jav=uint8(filter2(w,I)); Imed=medfilt2(I); Jmed=medfilt2(J); subplot('Position',[0,0.5,0.3,0.5]);imshow(I); subplot('Position',[0.33,0.5,0.3,0.5]);imshow(Iav); subplot('Position',[0.66,0.5,0.3,0.5]);imshow(Imed); subplot('Position',[0,0,0.3,0.5]);imshow(J); subplot('Position',[0.33,0,0.3,0.5]);imshow(Jav); subplot('Position',[0.66,0,0.3,0.5]);imshow(Jmed); end %中值滤波 %% 图像锐化 拉普拉斯算子 if 1==4 %拉普拉斯算子 I=imread('mold.tif'); L4=[0 -1 0;-1 4 -1;0 -1 0]; L8=[-1 -1 -1;-1 8 -1;-1 -1 -1]; IL4=uint8(filter2(L4,I)); IL8=uint8(filter2(L8,I)); subplot('Position',[0,0,0.3,1]);imshow(I); subplot('Position',[0.33,0,0.3,1]);imshow(IL4); subplot('Position',[0.66,0,0.3,1]);imshow(IL8); I0=imnoise(I,'gaussian',0,0.005); %叠加噪声 IL4=uint8(filter2(L4,I0)); IL8=uint8(filter2(L8,I0)); figure; subplot('Position',[0,0,0.3,1]);imshow(I0); subplot('Position',[0.33,0,0.3,1]);imshow(IL4); subplot('Position',[0.66,0,0.3,1]);imshow(IL8); end %拉普拉斯算子 %% sobel 锐化滤波 if 1==1 %sobel I=imread('mold.tif'); Sx=[-1 0 1;-2 0 2;-1 0 1]; %sobel算子 Sy=[-1 -2 -1;0 0 0;1 2 1]; Px=[-1 0 1;-1 0 1;-1 0 1]; %prewitt算子 Py=[-1 -1 -1;0 0 0;1 1 1]; Is=abs(filter2(Sx,I))+abs(filter2(Sy,I)); Ip=abs(filter2(Px,I))+abs(filter2(Py,I)); subplot('Position',[0,0,0.3,1]);imshow(I); subplot('Position',[0.33,0,0.3,1]);imshow(Is,[]); subplot('Position',[0.66,0,0.3,1]);imshow(Ip,[]); I0=imnoise(I,'gaussian',0,0.005); %叠加噪声 Is=abs(filter2(Sx,I0))+abs(filter2(Sy,I0)); Ip=abs(filter2(Px,I0))+abs(filter2(Py,I0)); figure; subplot('Position',[0,0,0.3,1]);imshow(I0); subplot('Position',[0.33,0,0.3,1]);imshow(Is,[]); subplot('Position',[0.66,0,0.3,1]);imshow(Ip,[]); end %sobel