数字图像实验二~四.doc

实验二%图像文件读取a=imread(lyy.tif);%图像写入imwrite(a,lyy.tif);%读取照片信息sizeofa=size(a);inf=imfinfo(lyy,tif);%显示照片imshow(a)%将彩图转换为灰度图I = imread(lyy.tif);B= rgb2gray(I);figure, imshow(B), figure, imshow(I);%灰度图像转化rgb=imread(lyy.tif);x1 map1=rgb2ind(rgb,64);x=ind2gray(x1,map1);imshow(x1,map1)figure,imshow(x)%调整灰度图像对比度clear all; close all;I=imread(lyy.tif);P=rgb2gray(I);J=imadjust(P, 0.2 0.5, 0 1);figure;subplot(131);%原图imshow(uint8(I);subplot(132);%灰度图imshow(uint8(P);subplot(133);%经过灰度变换后的灰度图imshow(uint8(J);%获取图像直方图p=imread(lyy.tif);i=rgb2gray(p);imhist(i)%直方图均衡化M = imread(lyy.tif);I=rgb2gray(M);J = histeq(I);imshow(I)figure, imshow(J)均衡化前的图像均衡化后的图像%直方图规范化close all; %关闭当前所有图形窗口，清空工作空间变量，清除工作空间所有变量clear all;clc;R=imread(lyy.tif);%读入原图像，赋值给RJ=rgb2gray(R); %将彩色图像数据R转换为灰度图像数据JM,N=size(J); %获得灰度图像数据J的行列数M，Nx=1;y=1; %定义行索引变量x、列索引变量yfor x=1:M for y=1:N if (J(x,y)35&J(x,y)75); H(x,y)=(105/180)*J(x,y)-75+150; end endendset(0,defaultFigurePosition,100,100,1000,500);%修改图形图像位置的默认设置set(0,defaultFigureColor,1 1 1)%修改图形背景颜色的设置subplot(121),imshow(J)%显示处理前后的图像subplot(122),imshow(H);规定化前的图像规定化后的图像%初始操作fn=imread(cameraman.tif);%读取图像%加噪声与噪声处理%加噪声I = imread(cameraman.tif);%原图像J = imnoise(I,salt & pepper,0.02);%加噪声J1=imnoise(I,gaussian);subplot(311),imshow(I)title(原图像)subplot(312), imshow(J)title(椒盐噪声)subplot(313)imshow(J1)title(高斯噪声)%处理噪声w4=fspecial(laplacian,0);g4=fn-imfilter(J,w4,replicate);g41=fn-imfilter(J,w4,symmetric);g42=fn-imfilter(J,w4,circular);g43=fn-imfilter(J1,w4,replicate);g44=fn-imfilter(J1,w4,symmetric);g45=fn-imfilter(J1,w4,circular);%显示椒盐噪声过滤效果效果subplot(424)imshow(fn)title(原图)subplot(421),imshow(g4)%replicate办法title(replicate办法处理椒盐噪声)subplot(422),imshow(g41)%symmetric办法title(symmetric办法处理椒盐噪声)subplot(423),imshow(g42)%circular办法title(circular办法处理椒盐噪声)subplot(425)imshow(g43)title(replicate办法处理高斯噪声)subplot(426)imshow(g44)title(symmetric办法处理高斯噪声)subplot(427)imshow(g45)title(circular办法处理高斯噪声)%对椒盐噪声做10次均值滤波H1= fspecial(average,10);jiao1 = imfilter(J,H1,replicate);subplot(211)imshow(J)title(加噪声图像)subplot(212)imshow(jiao1);title(10次均值滤波)%对椒盐噪声做20次均值滤波H2 = fspecial(average,20);jiao2 = imfilter(J,H2,replicate);imshow(J)title(加噪声图像)subplot(212)imshow(jiao2);title(20次均值滤波)%用中值滤波和均值滤波处理椒盐噪声I = imread(cameraman.tif);J = imnoise(I,salt & pepper,0.02);K = medfilt2(J);%中值滤波器H2 = fspecial(average,10);jiao3 = imfilter(I,H2,replicate);subplot(311)imshow(J),title(原图像 梁逸云)subplot(312),imshow(K)title(中值滤波)subplot(313)imshow(jiao3)title(均值滤波)%低通（平滑）滤波器(利用低通领域模板进行平滑)fn=imread(cameraman.tif);k=fspecial(average);kn=filter2(k,fn)/256;%3*3平滑滤波k1=fspecial(average,9);kn1=filter2(k1,fn)/255;%9*9平滑滤波%显示subplot(3,1,1);imshow(fn)title(原图 梁逸云)subplot(3,1,2);imshow(kn)title(3*3平滑滤波)subplot(3,1,3);imshow(kn1)title(9*9平滑滤波)实验三%锐化空间滤波%线性平滑滤波器（用3*3模板处理图像）w8=1 1 1;1 -8 1;1 1 1;%创建3*3矩阵g8=fn-imfilter(fn,w8,replicate);%3*3模板，边沿处理g82=fn-imfilter(fn,w8,symmetric);%5*5模板g25=genlaplacian(fn);%显示图像(3*3模板)subplot(3,1,1);imshow(fn)title(原图 梁逸云)subplot(3,1,2);imshow(g8)title(3*3处理后的图像 梁逸云)subplot(3,1,3);imshow(g82)title(3*3模板边沿处理的图像 梁逸云)%显示图像(5*5模板)subplot(211)imshow(fn)title(原图 梁逸云)subplot(212),imshow(g25)title(5*5处理后的图像 梁逸云)%锐化增强%产生5*5,9*9,15*15,25*25大小的拉普拉斯算子w55=ones(5);w55(3,3)=w55(3,3)-25;w99=ones(9);w99(5,5)=w99(5,5)-81;w15=ones(15);w15(8,8)=w15(8,8)-152;w25=ones(25);w25(13,13)=w25(13,13)-252;%利用算子g55=fn-imfilter(fn,w55,replicate);g99=fn-imfilter(fn,w99,replicate);g15=fn-imfilter(fn,w15,replicate);g25=fn-imfilter(fn,w25,replicate);%显示效果subplot(321),imshow(fn)title(原图像 梁逸云)subplot(322),imshow(g55)title(5*5模板 梁逸云)subplot(323),imshow(g99)title(9*9模板)subplot(324),imshow(g15)title(15*15模板 梁逸云)subplot(325),imshow(g25)title(25*25模板 梁逸云)%自行设计锐化滤波器进行锐化滤波I=imread(cameraman.tif);domain=8 8 0 8 8;8 8 0 8 8;0 0 0 0 0;8 8 0 8 8;8 8 0 8 8;K1=ordfilt2(I,5,domain);%显示原图与锐化滤波器效果，进行对比subplot(211)imshow(I)title(原图 梁逸云)subplot(212)imshow(K1)title(滤波后图像)附代码中使用的genlaplacian函数function g = genlaplacian(n)%UNTITLED3 此处显示有关此函数的摘要% 此处显示详细说明w25=1 1 1 1 1;1 1 1 1 1;1 1 -24 1 1;1 1 1 1 1;1 1 1 1 1;g=n-imfilter(n,w25,replicate);end实验四%读取原图像I=imread(camen.gif);J=imread(rice.gif);subplot(427)imshow(I)%显示图像title(camen.gif)subplot(428)imshow(J)%显示图像title(rice.gif)%对原图像加高斯噪声并显示subplot(421);I=imnoise(I,gaussian);imshow(I)title(加高斯噪声的camen.gif)subplot(422);J=imnoise(J,gaussian);imshow(J)title(加高斯噪声的rice.gif)title(加高斯噪声的rice.gif)%计算频谱幅值a=ffi(I);%用函数ffi做归一化具体函数文件见附函数文件ffia1=ffi(J);%用函数ffi做归一化具体函数文件见附函数文件ffi%subplot(423)imshow(a)%显示原图像频谱title(加高斯噪声的camen.gif频谱)subplot(424)imshow(a1)title(加高斯噪声的rice.gif频谱)%高斯滤波a=ffi(I);%用函数ffi做归一化具体函数文件见附函数文件ffia1=ffi(J);%用函数ffi做归一化具体函数文件见附函数文件ffinn=fspecial(gaussian,15,40);fe=imfilter(I,nn,replicate);fe1=imfilter(J,nn,replicate);subplot(425);imshow(fe)title(高斯滤波后camen.gif)subplot(426);imshow(fe1)title(高斯滤波后rice.gif)%高斯平滑滤波n1=3;sigma1=1.5;n2=3;sigma2=1.5;theta=0;I,map=imread(camen.gif);I=imnoise(I,gaussian);a=ffi(I);%用函数ffi做归一化具体函数文件见附函数文件ffir=cos(theta) -sin(theta); sin(theta) cos(theta);for i = 1 : n2 for j = 1 : n1 u = r*j-(n1+1)/2 i-(n2+1)/2;h(i,j)=exp(-u(1)2/(2*sigma12)/(sigma1*sqrt(2*pi)*exp(-u(2)2/(2*sigma22)/(sigma2*sqrt(2*pi); endendh = h / sqrt(sum(sum(h.*h);f1=convn(I,h,same);f2=convn(a,h,same);subplot(2,2,1); imagesc(I);title(camen.gif);colormap(gray);subplot(2,2,2);imagesc(f1);title(高斯平滑滤波后的camen1.gif(3x3);colormap(gray);subplot(2,2,3); imshow(a);title(camen.gif的频谱);colormap(gray);subplot(2,2,4);imshow(f2);title(高斯滤波平滑后的camen.gif(3x3)的频谱);colormap(gray);%高斯高通滤波I=imread(camen.gif);I=imnoise(I,gaussian);a=ffi(I);%用函数ffi做归一化具体函数文件见附函数文件ffiN,M=size(I);figure;subplot(2,2,1);imshow(I)title(源图像camen.gif );subplot(222);imshow(a)title(源图像camen.gif 频谱);n1=3;sigma1=0.5;n2=3;sigma2=0.5;theta=0;r=cos(theta) -sin(theta); sin(theta) cos(theta);for i = 1 : n2 for j = 1 : n1 u = r*j-(n1+1)/2 i-(n2+1)/2;h(i,j)=exp(-u(1)2/(2*sigma12)/(sigma1*sqrt(2*pi)*exp(-u(2)2/(2*sigma22)/(sigma2*sqrt(2*pi); endendh = h / sqrt(sum(sum(h.*h);f1=convn(I,h,same);f2=convn(a,h,same);t=ones(N,M);t=f1;for i=2:N-1 for j=2:M-1 f1(i,j)=t(i+1,j)+t(i-1,j)+t(i,j+1)+t(i,j-1)-4*t(i,j); endendt1=ones(N,M);t1=f2;for i=2:N-1 for j=2:M-1 f2(i,j)=t1(i+1,j)+t1(i-1,j)+t1(i,j+1)+t1(i,j-1)-4*t1(i,j); endendsubplot(2,2,3);imshow(f1);title(高斯高通滤波后-camen.gif );subplot(2,2,4);imshow(f2)title( 高斯高通滤波后-camen.gif的频谱 );%巴特沃斯低通滤波I=imread(camen.gif);I=imnoise(I,gaussian);figure;subplot(221);imshow(I);title(灰度图像);f=double(I);g=fft2(f);g=fftshift(g);F2=log(abs(g);subplot(222);imshow(F2,InitialMagnification,fit);title(灰度图像频谱图);colormap(jet);%colorbarresult F3 =bartworL( g );%用bartworL做滤波处理，具体函数见附函数bartworLsubplot(224);imshow(F3,InitialMagnification,fit);title(巴特沃斯低通滤波后的灰度图像频谱);colormap(jet);%colorbarresult=ifftshift(result);X2=ifft2(result);X3=uint8(real(X2);subplot(223);imshow(X3);title(巴特沃斯滤波后的灰度图像);%巴特沃斯高通滤波I=imread(camen.gif);I=imnoise(I,gaussian);subplot(221);imshow(I);title(灰度图像);f=double(I);g=fft2(f);g=fftshift(g);F2=log(abs(g);subplot(222);imshow(F2,InitialMagnification,fit);title(图像的频谱图);colormap(jet);%colorbarresult F3=bartworH(g);%用bartworH做滤波处理，具体函数见附函数bartworHsubplot(224);imshow(F3,InitialMagnification,fit);title(巴特沃斯滤波后的频谱图);colormap(jet);%colorbarresult=ifftshift(result);X2=ifft2(result);X3=uint8(real(X2);subplot(223);imshow(X3);title(巴特沃斯高通滤波后的图像);%理想低通滤波器I=imread(camen.gif);J=imnoise(I,gaussian,0,0.02);subplot(1,2,1);imshow(J);title(原图);f=double(J);g=fft2(f);g=fftshift(g);M,N=size(g);d0=100;m=fix(M/2);n=fix(N/2);for i=1:Mfor j=1:Nd=sqrt(i-m)2+(j-n)2);if (d=d0) h=1; else h=0;endresult(i,j)=h*g(i,j);endendr