基于小波变换的医学超声图像去噪方法研究程序.doc

I=imread('xian.bmp');
subplot(2,2,1);
imshow(I);
title('原始图像');
>>if~isempty(size(I,3))
y=rgb2gray(I);
end
>>subplot(2,2,2);
>>imshow(y);
>>title('原始灰度图像');
>>J=imnoise(y,'speckle');
>>subplot(2,2,3);
>>imshow(J);
>>title('加噪后的图像');
>>J=double(J);
>>A=log(1+J);
>>subplot(2,2,4);
>>imshow(A,[]);
>>title('对数变换后的图像');

I=imread('xian.bmp');
if~isempty(size(I,3))
y=rgb2gray(I);
end
subplot(2,2,1);
imshow(y);
title('原始灰度图像');
J=imnoise(y,'speckle');
subplot(2,2,2);
imshow(J);
title('加噪后的图像');
[m,n]=size(J);
J=double(J);
k1=filter2(fspecial('average',3),J)/255;%3*3均值滤波
k2=filter2(fspecial('average',7),J)/255;%7*7均值滤波
subplot(2,2,3);
imshow(k1,[]);
title('3*3均值滤波');
subplot(2,2,4);
imshow(k2,[]);
title('7*7均值滤波');
[PSNR1,MSE1]=psnr(y,k1);
[PSNR2,MSE2]=psnr(y,k2);
display('MSE1:');
MSE1
display('PSNR1:');
PSNR1
display('MSE2:');
MSE2
display('PSNR2:');
PSNR2
MSE1:

MSE1=

1.0948e+004

PSNR1:

PSNR1=

7.7376

MSE2:

MSE2=

1.0948e+004

PSNR2:

PSNR2=

7.7373

I=imread('xian.bmp');
if~isempty(size(I,3))
y=rgb2gray(I);
end
subplot(2,2,1);
imshow(y);
title('原始灰度图像');
J=imnoise(y,'speckle');
subplot(2,2,2);
imshow(J);
title('加噪后的图像');
[m,n]=size(J);
J=double(J);
x1=medfilt2(J,[33]);%3*3中值滤波
x2=medfilt2(J,[77]);%7*7中值滤波
subplot(2,2,3);
imshow(x1,[]);
title('3*3中值滤波');
subplot(2,2,4);
imshow(x2,[]);
title('7*7中值滤波');
[PSNR1,MSE1]=psnr(y,x1);
[PSNR2,MSE2]=psnr(y,x2);
display('MSE1:');
MSE1
display('PSNR1:');
PSNR1
display('MSE2:');
MSE2
display('PSNR2:');
PSNR2
MSE1:

MSE1=

156.7310

PSNR1:

PSNR1=

26.1793

MSE2:

MSE2=

99.1610

PSNR2:

PSNR2=

28.1674

closeall;
clc
I=imread('xian.bmp');
if~isempty(size(I,3))
y=rgb2gray(I);
end
J=imnoise(y,'speckle');
[m,n]=size(J);
J=double(J);
c1=wiener2(J,[33]);%3*3维纳滤波
c2=wiener2(J,[77]);%7*7维纳滤波
figure;
subplot(2,2,1);
imshow(y,[]);
title('原始灰度图像');
subplot(2,2,2);
imshow(J,[]);
title('加噪后的图像');
subplot(2,2,3);
imshow(c1,[]);
title('3*3维纳滤波');
subplot(2,2,4);
imshow(c2,[]);
title('7*7维纳滤波');
[PSNR1,MSE1]=psnr(y,c1);
[PSNR2,MSE2]=psnr(y