数字图像处理实验报告——图像复原实验

实验报告

课程名称数字图像处理导论

专业班级_______________

姓名_______________

学号_______________

电气与信息学院

和谐勤奋求是创新

2.对加入噪声图像选用不同的平滑（低通）模板做运算，对比不同模板所形成的效果，要求在同

一窗口中显示。

I=imread('moon.tif');

H = fspecial('sobel');

subplot(2,2,1)

imshow(I);

title(' Qriginal Image ');

Sobel = imfilter(I,H,'replicate');

subplot(2,2,2)

imshow(Sobel);

title(' Sobel Image ')

H = fspecial('laplacian',0.4);

lap = imfilter(I,H,'replicate');

subplot(2,2,3)

imshow(lap);

title(' Laplacian Image ')

H = fspecial('gaussian',[3 3],0.5);

gaussian = imfilter(I,H,'replicate');

subplot(2,2,4)

imshow(gaussian);

title(' Gaussian Image ')

3.使用函数imfilter时，分别采用不同的填充方法（或边界选项，如零填

充、’replicate’、’symmetric’、’circular’）进行低通滤波，显示处理后的图像。

originalRGB = imread('trees.tif');

subplot(3,2,1)

imshow(originalRGB);

title(' Qriginal Image ');

h = fspecial('motion', 50, 45); %motion blurred

filteredRGB = imfilter(originalRGB, h);

subplot(3,2,2)

imshow(filteredRGB);

title(' Motion Blurred Image ');

boundaryReplicateRGB = imfilter(originalRGB, h, 'replicate');

subplot(3,2,3)

imshow(boundaryReplicateRGB);

title(' 0-Padding');

boundary0RGB = imfilter(originalRGB, h, 0);

subplot(3,2,4)

imshow(boundary0RGB);

title('Replicate');

boundarysymmetricRGB = imfilter(originalRGB, h, 'symmetric'); subplot(3,2,5)

imshow(boundarysymmetricRGB);

title(' Symmetric ');

boundarycircularRGB = imfilter(originalRGB, h, 'circular'); subplot(3,2,6)

imshow(boundarycircularRGB);

title(' Circular');

5.对加入椒盐噪声的图像分别采用均值滤波法，和中值滤波法对有噪声的图像做处理，要求在同

一窗口中显示结果。

I=imread('trees.tif');

J = imnoise(I,'salt & pepper',0.05);

subplot(1,3,1)

imshow(J);

title(' Original Image ');

h=fspecial('average'); %Averaging Filtering

J1=imfilter(J,h);

subplot(1,3,2)

imshow(J1);

title(' Averaging Filtering ');

J2=medfilt2(J); %Median Filtering subplot(1,3,3)

imshow(J2);

title(' Median Filtering ');

附录：可能用到的函数和参考结果**************报告里不能用参考结果中的图像

1)读出eight.tif这幅图像，给这幅图像分别加入椒盐噪声和高斯噪声后并与前一张

图显示在同一图像窗口中。

I=imread('cameraman.tif');

subplot(1,3,1)

imshow(I);

title(' Qriginal Image ');

J = imnoise(I,'salt & pepper',0.05); %noise density=0.05

subplot(1,3,2)

imshow(J);

title(' salt & pepper ');

K= imnoise(I,'gaussian',0.01,0.01);

subplot(1,3,3)

imshow(K);

title(' gaussian ');

图2.1 初始图像及椒盐噪声图像、高斯噪声污染图

2)对加入噪声图像选用不同的平滑（低通）模板做运算，对比不同模板所形成的效

果，要求在同一窗口中显示。

I=imread('trees.tif');

H = fspecial('sobel');

subplot(2,2,1)

imshow(I);

title(' Qriginal Image ');

Sobel = imfilter(I,H,'replicate');

subplot(2,2,2)

imshow(Sobel);

title(' Sobel Image ')

H = fspecial('laplacian',0.4);

lap = imfilter(I,H,'replicate');

subplot(2,2,3)

imshow(lap);

title(' Laplacian Image ')

H = fspecial('gaussian',[3 3],0.5);