图像的退化与复原.doc

(1) 进入Matlab6.x软件实验平台(2) 读取Lena图像并显示。I=imread(lena.jpg);imshow(I); (3) 设计运动模糊滤波器、设计高斯模糊噪声滤波器。运动模糊滤波器:I=imread(lena.jpg); noise=0.1*randn(size(I); psf=fspecial(motion,21,11); blurred=imfilter(I,psf,circular); subplot(1,2,2),imshow(blurred); subplot(1,2,1),imshow(I);高斯模糊噪声滤波器:I=imread(lena.jpg); noise=0.1*randn(size(I); psf=fspecial(gaussian,21,11); blurred=imfilter(I,psf,circular); subplot(1,2,2),imshow(blurred); subplot(1,2,1),imshow(I); (4) 生成退化或降质图像并显示。运动模糊:高斯模糊噪声: (5) 修改相关滤波器参数，观察图像退化或降质程度。运动模糊滤波器修改参数:I=imread(lena.jpg); noise=0.1*randn(size(I); psf=fspecial(motion,10,11); blurred=imfilter(I,psf,circular); subplot(1,2,2),imshow(blurred); subplot(1,2,1),imshow(I);高斯模糊噪声滤波器修改参数:I=imread(lena.jpg); noise=0.1*randn(size(I); psf=fspecial(gaussian,10,11); blurred=imfilter(I,psf,circular); subplot(1,2,2),imshow(blurred); subplot(1,2,1),imshow(I); (6) 设计逆滤波器，并对降质图像进行复原，比较复原图像与原始图像。对运动模糊图像进行复原:I=imread(lena.jpg); LEN=10; THETA=10; PSF=fspecial(motion,LEN,THETA); Blurredmotion=imfilter(I,PSF,circular,conv);subplot(2,2,1),imshow(I)subplot(2,2,2),imshow(Blurredmotion); wnr1=deconvwnr(Blurredmotion,PSF); subplot(2,2,3),imshow(wnr1);对高斯模糊噪声图像进行复原:I=imread(lena.jpg); LEN=10; THETA=10; PSF=fspecial(gaussian,LEN,THETA); Blurredmotion=imfilter(I,PSF,circular,conv);subplot(2,2,1),imshow(I)subplot(2,2,2),imshow(Blurredmotion); wnr1=deconvwnr(Blurredmotion,PSF); subplot(2,2,3),imshow(wnr1); (7) 设计维纳滤波器，并对降质图像进行复原，比较复原图像与原始图像。对运动模糊图像进行复原:I = imread(lena.jpg);subplot(2,2,1),imshow(I);len = 30;theta = 75;PSF = fspecial(motion,len,theta);J = imfilter(I,PSF,conv,circular);subplot(2,2,2),imshow(J);wiener_img = deconvwnr(J,PSF);subplot(2,2,3),imshow(wiener_img);对高斯模糊噪声图像进行复原: I = imread(lena.jpg); subplot(2,2,1),imshow(I); len = 30; theta = 75; PSF = fspecial(gaussian,len,theta); J = imfilter(I,PSF,conv,circular); subplot(2,2,2),imshow(J); wiener_img = deconvwnr(J,PSF); subplot(2,2,3),imshow(wiener_img); (8) 计算退化图像、不同方法复原后图像的信噪比。I=imread(lena.jpg); LEN=10; THETA=10; PSF=fspecial(gaussian,LEN,THETA); Blurredmotion=imfilter(I,PSF,circular,conv);wnr1=deconvwnr(Blurredmotion,PSF); Sn=abs(fft2(gaussian).2; % 噪声功率谱nA=sum(Sn(:)/prod(size(gauss