二维高斯低通滤波器matlab程序设计

1、二维高斯滤波器图像滤波MTATLAB程序设计用MATLAB设计一个3X3模板标准差为0.5,1.5,2.5的二维高斯低通滤波器（Gaussionlowpassfilter分别对灰度图像，真彩色图像，伪彩色图像进彳丁滤波处理%二维高斯低通滤波器%文件为glpf.mfunctionglpf(J)%处理索引图像ifisind(J)I,map=imread(J);I=imnoise(I,gaussian,0.005);subplot(2,2,1)imshow(I,map);title(a.原始图像);K1=filter2(fspecial(gaussian,3*3,0.5),I);K2=filter2

2、(fspecial(gaussian,3*3,1.5),I);K3=filter2(fspecial(gaussian,3*3,2.5),I);subplot(2,2,2)imshow(K1,map);title(b.滤波器3*3,sigma=0.5)subplot(2,2,3)imshow(K2,map);title(c.滤波器3*3,sigma=1.5)subplot(2,2,4)imshow(K3,map);title(d.滤波器3*3,sigma=2.5)end%处理灰度,真彩色图像ifisind(J)J=imread(J);%读入图像I=imnoise(J,gaussian);%加入

3、高斯噪声%输出原始图像subplot(2,2,1)imshow(I);title(a.原始图像)hl=fspecial(gaussian,3,3,0.5);%用预定义的gaussian函数mnp=size(I);%mnpm,n代表像素点的位置,p代表空间分量%p=1,代表亮度分量，即灰度图像%p=3，代表亮度分量(Y),色差分量(Cr,Cb)ifp=1%处理灰度图像I=double(I);I=conv2(I,h1,same);%I与h的二维离散卷积endifp=3%处理真彩色I=double(I);I(:,:,1)=conv2(I(:,:,1),h1,same);I(:,:,2)=conv2(

4、I(:,:,2),h1,same);I(:,:,3)=conv2(I(:,:,3),h1,same);endI=uint8(I);%8位无符号整型%经过3*3,sigma=0.5二维高斯低通滤波器滤波后的图像subplot(2,2,2)imshow(I);title(b.滤波器3*3,sigma=0.5)h2=fspecial(gaussian,3,3,1.5);mnp=size(I);ifp=1I=double(I);I二conv2(I,h2,same);%二维离散卷积endifp=3I=double(I);I(:,:,1)=conv2(I(:,:,1),h2,same);I(:,:,2)=

5、conv2(I(:,:,2),h2,same);I(:,:,3)=conv2(I(:,:,3),h2,same);endI=uint8(I);%经过3*3，sigma=1.5二维高斯低通滤波器滤波后的图像subplot(2,2,3)imshow(I);title(c.滤波器3*3,sigma=1.5)h3=fspecial(gaussian,3,3,2.5);mnp=size(I);ifp=1I=double(I);I=conv2(I,h3,same);endifp=3I=double(I);I(:,:,1)=conv2(I(:,:,1),h3,same);I(:,:,2)=conv2(I(:,:,2),h3,same);I(:,:,3)=conv2(I(:,:,3),h3,same);endI=uint8(I);%经过3*3，sigma=2.5二维高斯低通滤波器滤波后的图像subplot(2,2,4)imshow(I);title（d.滤波器3*3,sigma=2.5）end程序调用%glpfUse.m%调用functionglpf（）处理灰度，真彩色，索引（伪彩色）图像并绘图gl