关键字
代码
I=imread('6.bmp');
noise=0.18*randn(size(I));
psf=fspecial('motion',21,11);
blurred=imfilter(I,psf,'circular');
>> blurrednoisy=im2uint8(blurred+noise);
??? Error using ==> plus
Integers can only be combined with integers of the same class, or scalar doubles.
>>
figure,imshow(noise);
figure,imshow(blurred);
>>
实验和结果情况:
>> size(I)
ans =
512 512 3
>> info=imfinfo('6.bmp');
>> info
info =
Filename: '6.bmp'
FileModDate: '13-May- 15:26:56'
FileSize: 786486
Format: 'bmp'
FormatVersion: [1x33 char]
Width: 512
Height: 512
BitDepth: 24
ColorType: 'truecolor'
FormatSignature: 'BM'
NumColormapEntries: 0
Colormap: []
RedMask: []
GreenMask: []
BlueMask: []
ImageDataOffset: 54
BitmapHeaderSize: 40
NumPlanes: 1
CompressionType: 'none'
BitmapSize: 786432
HorzResolution: 0
VertResolution: 0
NumColorsUsed: 0
NumImportantColors: 0
E1=mat2gray(I(:,:,1));
noise=0.1*randn(size(E1));
psf1=fspecial('motion',21,11);
blurred1=imfilter(E1,psf1,'circular');
burrednoisy1=im2uint8(blurred1+noise);
E2=mat2gray(I(:,:,2));
blurred2=imfilter(E2,psf1,'circular');
burrednoisy2=im2uint8(blurred2+noise);
E3=mat2gray(I(:,:,3));
blurred3=imfilter(E3,psf1,'circular');
burrednoisy3=im2uint8(blurred3+noise);
burrednoisy(:,:,1)=burrednoisy1;
burrednoisy(:,:,2)=burrednoisy2;
burrednoisy(:,:,3)=burrednoisy3;
figure,imshow(burrednoisy);
这样就实现效果如下:
NP=abs(fftn(noise)).^2; %噪声功率
NPOW=sum(NP(:))/prod(size(noise)); %噪声自相关
NCORR=fftshift(real(ifftn(NP)));
IP1=abs(fftn(E1)).^2; %R分量图像功率
IPOW1=sum(IP1(:))/prod(size(E1)); %R分量图像自相关
IPORR1=fftshift(real(ifftn(IP1)));
IPORRC1=IPORR1( :,ceil(size(E1,1)/2));
IP2=abs(fftn(E2)).^2; %G分量图像功率
IPOW2=sum(IP2(:))/prod(size(E2)); %G分量图像自相关
IPORR2=fftshift(real(ifftn(IP2)));
IPORRC2=IPORR2( :,ceil(size(E2,1)/2));
IP3=abs(fftn(E3)).^2; %B分量图像功率
IPOW1=sum(IP3(:))/prod(size(E3)); %B分量图像自相关
IPORR3=fftshift(real(ifftn(IP3)));
IPORRC3=IPORR3( :,ceil(size(E3,1)/2));
q(:,:,1)=deconvwnr(burrednoisy1,psf,NCORR,IPORR1);
q(:,:,2)=deconvwnr(burrednoisy2,psf,NCORR,IPORR2);
q(:,:,3)=deconvwnr(burrednoisy3,psf,NCORR,IPORR3);
figure,imshow(q);
title('deconvwnr(burrednoisy,psf,NCORR,IPORR)')
v(:,:,1)=deconvwnr(burrednoisy1,psf,NCORR,IPORRC1);
v(:,:,2)=deconvwnr(burrednoisy2,psf,NCORR,IPORRC2);
v(:,:,3)=deconvwnr(burrednoisy3,psf,NCORR,IPORRC3);
figure,imshow(v);
title('deconvwnr(burrednoisy,psf,NCORR,IPORRC)')
实现效果如下:
遗憾的是,当移植到一幅彩色图像时候,出错,如下
错误点1
>> E1=mat2gray(I(:,:,1));
>> noise=0.1*randn(size(E1));
>> psf1=fspecial('motion',21,11);
>> blurred1=imfilter(E1,psf1,'circular');
>> burrednoisy1=im2uint8(blurred1+noise);
>> E2=mat2gray(I(:,:,2));
>> blurred2=imfilter(E2,psf1,'circular');
>> burrednoisy2=im2uint8(blurred2+noise);
>> E3=mat2gray(I(:,:,3));
>> blurred3=imfilter(E3,psf1,'circular');
>> burrednoisy3=im2uint8(blurred3+noise);
>> burrednoisy(:,:,1)=burrednoisy1;
??? Subscripted assignment dimension mismatch.
info=imfinfo('fly.bmp')
info =
Filename: 'fly.bmp'
FileModDate: '16-May- 10:16:42'
FileSize: 856374
Format: 'bmp'
FormatVersion: [1x33 char]
Width: 640
Height: 446
BitDepth: 24
ColorType: 'truecolor'
FormatSignature: 'BM'
NumColormapEntries: 0
Colormap: []
RedMask: []
GreenMask: []
BlueMask: []
ImageDataOffset: 54
BitmapHeaderSize: 40
NumPlanes: 1
CompressionType: 'none'
BitmapSize: 856320
HorzResolution: 0
VertResolution: 0
NumColorsUsed: 0
NumImportantColors: 0
可以导致错误2
>> figure,imshow(burrednoisy1);
>> burrednoisy1=mat2gray(burrednoisy1);
>> burrednoisy(:,:,1)=burrednoisy1;
??? Subscripted assignment dimension mismatch. 所以,这里问题真是很大很大,搞不明白为什么这里会出错
可以导致错误3:
>> I=imread('fly.bmp');
>> E1=I(:,:,1);
>> figure,imshow(E1);
>> noise=0.1*randn(size(E1));
>> psf1=fspecial('motion',21,11);
>> blurred1=imfilter(E1,psf1,'circular');
>> burrednoisy1=im2uint8(blurred1+noise);
??? Error using ==> plus
Integers can only be combined with integers of the same class, or scalar doubles.
测试分析:
>> size(burrednoisy2)
ans =
446 640
>> size(blurred2)
ans =
446 640
>>
>> burrednoisy=zeros(size(I));
>> size(burrednoisy)
ans =
446 640 3
>>
结果是ok:
>> burrednoisy(:,:,1)=burrednoisy1; >>
恐怕上述问题在于缺少了这个burrednoisy=zeros(size(I));
可是,运行结果还是问题大得不可理喻:
I=imread('fly.bmp');
burrednoisy=zeros(size(I));
q=zeros(size(I));
E1=mat2gray(I(:,:,1));
noise=0.1*randn(size(E1));
psf1=fspecial('motion',21,11);
blurred1=imfilter(E1,psf1,'circular');
burrednoisy1=im2uint8(blurred1+noise);
E2=mat2gray(I(:,:,2));
blurred2=imfilter(E2,psf1,'circular');
burrednoisy2=im2uint8(blurred2+noise);
E3=mat2gray(I(:,:,3));
blurred3=imfilter(E3,psf1,'circular');
burrednoisy3=im2uint8(blurred3+noise);
burrednoisy(:,:,1)=burrednoisy1;
burrednoisy(:,:,2)=burrednoisy2;
burrednoisy(:,:,3)=burrednoisy3;
figure,imshow(burrednoisy);
NP=abs(fftn(noise)).^2; %噪声功率
NPOW=sum(NP(:))/prod(size(noise)); %噪声自相关
NCORR=fftshift(real(ifftn(NP)));
IP1=abs(fftn(E1)).^2; %R分量图像功率
IPOW1=sum(IP1(:))/prod(size(E1)); %R分量图像自相关
IPORR1=fftshift(real(ifftn(IP1)));
IPORRC1=IPORR1( :,ceil(size(E1,1)/2));
IP2=abs(fftn(E2)).^2; %G分量图像功率
IPOW2=sum(IP2(:))/prod(size(E2)); %G分量图像自相关
IPORR2=fftshift(real(ifftn(IP2)));
IPORRC2=IPORR2( :,ceil(size(E2,1)/2));
IP3=abs(fftn(E3)).^2; %B分量图像功率
IPOW1=sum(IP3(:))/prod(size(E3)); %B分量图像自相关
IPORR3=fftshift(real(ifftn(IP3)));
IPORRC3=IPORR3( :,ceil(size(E3,1)/2));
q(:,:,1)=deconvwnr(burrednoisy1,psf,NCORR,IPORR1);
q(:,:,2)=deconvwnr(burrednoisy2,psf,NCORR,IPORR2);
q(:,:,3)=deconvwnr(burrednoisy3,psf,NCORR,IPORR3);
figure,imshow(q);
title('deconvwnr(burrednoisy,psf,NCORR,IPORR)')
实验2
>> clear
>> I=imread('fly.bmp');
>> E1=mat2gray(I(:,:,1));
>> burrednoisy(:,:,1)=E1;
>> E2=mat2gray(I(:,:,2));
>> burrednoisy(:,:,2)=E2;
>> E3=mat2gray(I(:,:,3));
>> burrednoisy(:,:,3)=E3;
>> figure,imshow(burrednoisy);
实验2 :
>> I=imread('fly.bmp');
>> E1=mat2gray(I(:,:,1));
>> noise=0.1*randn(size(E1));
>> psf1=fspecial('motion',21,11);
blurred1=imfilter(E1,psf1,'circular');
burrednoisy1=im2uint8(blurred1+noise);
>> burrednoisy(:,:,1)=burrednoisy1;
成功了
天不负有心人啊,终于搞出个名堂;
I=imread('fly.bmp');
E1=mat2gray(I(:,:,1));
noise=0.1*randn(size(E1));
psf1=fspecial('motion',21,11);
blurred1=imfilter(E1,psf1,'circular');
burrednoisy1=im2uint8(blurred1+noise);
burrednoisy(:,:,1)=burrednoisy1;
E2=mat2gray(I(:,:,2));
blurred2=imfilter(E2,psf1,'circular');
burrednoisy2=im2uint8(blurred2+noise);
burrednoisy(:,:,2)=burrednoisy2;
E3=mat2gray(I(:,:,3));
blurred3=imfilter(E3,psf1,'circular');
burrednoisy3=im2uint8(blurred3+noise);
burrednoisy(:,:,3)=burrednoisy3;
figure,imshow(burrednoisy);
区别仅仅在于
burrednoisy(:,:,x)=burrednoisyx位置
>> NP=abs(fftn(noise)).^2; %噪声功率
NPOW=sum(NP(:))/prod(size(noise)); %噪声自相关
NCORR=fftshift(real(ifftn(NP)));
IP1=abs(fftn(E1)).^2; %R分量图像功率
IPOW1=sum(IP1(:))/prod(size(E1)); %R分量图像自相关
IPORR1=fftshift(real(ifftn(IP1)));
>> q(:,:,1)=deconvwnr(burrednoisy1,psf,NCORR,IPORR1);
??? Undefined function or variable 'psf'.
>> q(:,:,1)=deconvwnr(burrednoisy1,psf1,NCORR,IPORR1);
>> IP2=abs(fftn(E2)).^2; %G分量图像功率
IPOW2=sum(IP2(:))/prod(size(E2)); %G分量图像自相关
IPORR2=fftshift(real(ifftn(IP2)));
>> q(:,:,2)=deconvwnr(burrednoisy2,psf1,NCORR,IPORR2);
>> IP3=abs(fftn(E3)).^2; %B分量图像功率
IPOW1=sum(IP3(:))/prod(size(E3)); %B分量图像自相关
IPORR3=fftshift(real(ifftn(IP3)));
>> q(:,:,3)=deconvwnr(burrednoisy3,psf1,NCORR,IPORR3);
>> figure,imshow(q);
title('deconvwnr(burrednoisy,psf,NCORR,IPORR)')
这个结果有点怪,不知对不对.
对第三个图像处理,悟出刚才一些问题:为什么会出现 ??? Subscripted assignment dimension mismatch.
解决方法就是一句一句写入,或者用m文件
实验2 比较 fspecial('motion',x,y);
>> clear
>> I=imread('audi.jpg');
>> E1=mat2gray(I(:,:,1));
>> noise=0.1*randn(size(E1));
>> psf1=fspecial('motion',21,11);
>> blurred1=imfilter(E1,psf1,'circular');
>> burrednoisy1=im2uint8(blurred1+noise);
>> burrednoisy(:,:,1)=burrednoisy1;
>> E2=mat2gray(I(:,:,2));
>> blurred2=imfilter(E2,psf1,'circular');
>> burrednoisy(:,:,2)=burrednoisy2;
??? Undefined function or variable 'burrednoisy2'.
>> burrednoisy2=im2uint8(blurred2+noise);
>> burrednoisy(:,:,2)=burrednoisy2;
>> E3=mat2gray(I(:,:,3));
>> blurred3=imfilter(E3,psf1,'circular');
>> burrednoisy3=im2uint8(blurred3+noise);
>> burrednoisy(:,:,3)=burrednoisy3;
>> figure,imshow(burrednoisy);
>> psf1=fspecial('motion',41,31);
>> blurred1=imfilter(E1,psf1,'circular');
>> burrednoisy1=im2uint8(blurred1+noise);
>> burrednoisy(:,:,1)=burrednoisy1;
>> E2=mat2gray(I(:,:,2));
>> blurred2=imfilter(E2,psf1,'circular');
>> burrednoisy2=im2uint8(blurred2+noise);
>> burrednoisy(:,:,2)=burrednoisy2;
>> E3=mat2gray(I(:,:,3));
>> blurred3=imfilter(E3,psf1,'circular');
>> burrednoisy3=im2uint8(blurred3+noise);
>> burrednoisy(:,:,3)=burrednoisy3;
>> figure,imshow(burrednoisy);
非常遗憾,仍然有大量细节无法修复出来.
幸运的是,及时上网得到一幅非常不错的图片
http://www-rohan.sdsu.edu/doc/matlab/toolbox/images/deblurr6.html 一个不错的网站,效果好是因为没有加噪声
>> I = imread('audi.jpg');
>> figure;imshow(I);title('Original Image');
>> % create PSF
LEN = 31;
THETA = 11;
PSF = fspecial('motion',LEN,THETA);
% blur the image
Blurred = imfilter(I,PSF,'circular','conv');
figure; imshow(Blurred);title('Blurred Image');
% deblur the image
wnr1 = deconvwnr(Blurred,PSF);
figure;imshow(wnr1);
title('Restored, True PSF');
>>
最后,为了验证噪声的作用到底有多大,我们可以用灰度图像做两个实验,一个用后一种没有噪声进行,一个用书上的,看看效果怎样,比较就知道了
