空域、频域图像增强举例

1、MATLAB图像增强程序举例1.灰度变换增强程序：% GRAY TRANSFORMclc;I=imread('pout.tif');imshow(I);J=imadjust(I,0.3 0.7,0 1,1);  %transforms the walues in the %intensity image I to values in J by linealy mapping values% between 0.3 and 0.7 to values between 0 and 1.figure;imshow(J);J=imadjust(I,0.3 0.7,0

2、 1,0.5);  % if GAMMA is less than 1,the% mapping si weighted toward higher (brighter) output values.figure;imshow(J);J=imadjust(I,0.3 0.7,0 1,1.5);  % if GAMMA is greater than% 1,the mapping si weighted toward lower (darker) output values.figure;imshow(J)J=imadjust(I,0.3 0.7,0 1,

3、1);  % If TOP<BOTTOM,the output% image is reversed,as in a photographic negative.figure;imshow(J);5.bmp (587.92 KB)2008-7-18 08:252.直方图灰度变换%直方图灰度变换X,map=imread('forest.tif');I=ind2gray(X,map);%把索引图像转换为灰度图像imshow(I);title('原图像');improfile%用鼠标选择一条对角线，显示线段的灰度值figure;subplot

4、(121)plot(0:0.01:1,sqrt(0:0.01:1)axis squaretitle('平方根灰度变换函数')subplot(122)maxnum=double(max(max(I);%取得二维数组最大值J=sqrt(double(I)/maxnum);%把数据类型转换成double,然后进行平方根变换%sqrt函数不支持uint8类型J=uint8(J*maxnum);%把数据类型转换成uint8类型imshow(J)title('平方根变换后的图像')3.直方图均衡化程序举例% HISTGRAM EAQUALIZATIONclc;% Clear

5、 command windowI=imread('tire.tif');% reads the image in tire.tif into Iimshow(I);% displays the intensity image I with 256 gray levelsfigure;%creates a new figure windowimhist(I);% displays a histogram for the intensity image IJ=histeq(I,64);% transforms the intensity image I,returning J an

6、 intensityfigure;%image with 64 discrete levelsimshow(J);figure;imhist(J);J=histeq(I,32);%transforms the intensity image ,returning in % J an intensityfigure;%image with 32 discrete levelsimshow(J);figure;imhist(J);4.直方图规定化程序举例% HISTGRAM REGULIZATIONclc; %Clear command windowI=imread('tire.tif&#

7、39;);%reads the image in tire.tif into IJ=histeq(I,32);%transforms the intensity image I,returning in%J an intensity image with 32 discrete levelscounts,x=imhist(J);%displays a histogram for the intensity image IQ=imread('pout.tif');%reads the image in tire.tif into Ifigure;imshow(Q);figure;

8、imhist(Q);M=histeq(Q,counts);%transforms the intensity image Q so that the%histogram of the output image M approximately matches countsfigure;imshow(M);figure;imhist(M);空域滤波增强部分程序1.线性平滑滤波I=imread('eight.tif');J=imnoise(I,'salt & pepper',0.02);subplot(221),imshow(I)title('原图像&

9、#39;)subplot(222),imshow(J)title('添加椒盐噪声图像')K1=filter2(fspecial('average',3),J)/255;%应用3*3邻域窗口法 subplot(223),imshow(K1)title('3x3窗的邻域平均滤波图像')K2=filter2(fspecial('average',7),J)/255;%应用7*7邻域窗口法 subplot(224),imshow(K2)title('7x7窗的邻域平均滤波图像')5.bmp (689.12 KB)2008-

10、7-18 09:502.中值滤波器MATLAB中的二维中值滤波函数medfit2来进行图像中椒盐躁声的去除%IMAGE NOISE REDUCTION WITH MEDIAN FILTERclc;hood=3;%滤波窗口I,map=imread('eight.tif');imshow(I,map);noisy=imnoise(I,'salt & pepper',0.05);figure;imshow(noisy,map);filtered1=medfilt2(noisy,hood hood);figure;imshow(filtered1,map);ho

11、od=5;filtered2=medfilt2(noisy,hood hood);figure;imshow(filtered2,map);hood=7;filtered3=medfilt2(noisy,hood hood);figure;imshow(filtered3,map);3.  4邻域8邻域平均滤波算法% IMAGE NOISE REDUCTION WITH MEAN ALGORITHMclc;I,map=imread('eight.tif');noisy=imnoise(I,'salt & pepper',0.05);m

12、yfilt1=0 1 0;1 1 1;0 1 0;%4邻域平均滤波模版myfilt1=myfilt1/9;%对模版归一化filtered1=filter2(myfilt1,noisy);imshow(filtered1,map);myfilt2=1 1 1;1 1 1;1 1 1;myfilt2=myfilt2/9;filtered2=filter2(myfilt2,noisy);figure;imshow(filtered2,map);频域增强程序举例1.低通滤波器% LOWPASS FILTERclc;I,map=imread('eight.tif');noisy=imno

13、ise(I,'gaussian',0.05);imshow(noisy,map);myfilt1=1 1 1;1 1 1;1 1 1;myfilt1=myfilt1/9;filtered1=filter2(myfilt1,noisy);figure;imshow(filtered1,map);myfilt2=1 1 1;1 2 1;1 1 1;myfilt2=myfilt2/10;filtered2=filter2(myfilt2,noisy);figure;imshow(filtered2,map);myfilt3=1 2 1;2 4 2; 1 2 1;myfilt3=fil

14、ter2(myfilt3,noisy);figure;imshow(filtered3,map);2.布特沃斯低通滤波器图像实例I=imread('saturn.png');J=imnoise(I,'salt & pepper',0.02);subpolt(121),imshow(J)subplot(121),imshow(J)title('含噪声的原图像')%- 08-7-18  上午10:37 -%I=imread('saturn.png');J=imnoise(I,'salt & pepper',0.02);subpolt(121),imshow(J)subplot(121),imshow(J)title('含噪声的原图像')clc;I=imread('saturn.png');J=imnoise(I,'salt & pepper',0.02);subplot(121),imshow(J)title('含噪声的原图像')J=double(J);f=fft2(J);g=fftshift(f)