Matlab傅里叶变换模和相位和各种滤波处理.docx

Matlab傅里叶变换模和相位和各种滤波处理傅里叶变换模和相位img=imread(h:\img.png);f=fft2(img); %傅里叶变换f=fftshift(f); %使图像对称r=real(f); %图像频域实部i=imag(f); %图像频域虚部margin=log(abs(f)); %图像幅度谱，加log便于显示phase=log(angle(f)*180/pi); %图像相位谱l=log(f); subplot(2,2,1),imshow(img),title(源图像);subplot(2,2,2),imshow(l,[]),title(图像频谱);subplot(2,2,3),imshow(margin,[]),title(图像幅度谱);subplot(2,2,4),imshow(phase,[]),title(图像相位谱);添加高斯噪声、四阶巴特沃斯低通滤波I=imread(h:\img.png); x=rgb2gray(I);y1=imnoise(x,gaussian,0,0.02); f=double(y1); % 数据类型转换，MATLAB不支持图像的无符号整型的计算g=fft2(f); % 傅立叶变换g=fftshift(g); % 转换数据矩阵[M,N]=size(g);nn=4; % 四阶巴特沃斯(Butterworth)低通滤波器d0=50; %截止频率为50m=fix(M/2); n=fix(N/2);for i=1:M for j=1:N d=sqrt((i-m)^2+(j-n)^2); h=1/(1+0.414*(d/d0)^(2*nn)); % 计算低通滤波器传递函数 result(i,j)=h*g(i,j); endendresult=ifftshift(result);y2=ifft2(result);y3=uint8(real(y2));subplot(1,2,1),imshow(y1),title(添加高斯噪声后的图像);subplot(1,2,2),imshow(y3),title(四阶巴特沃斯低通滤波图像);维纳滤波I=imread(h:\img.png); x=rgb2gray(I);J1=imnoise(x,gaussian,0,0.02); %给图像添加高斯噪声J2=imnoise(x,salt pepper,0.02);%给图像添加椒盐噪声J3=imnoise(x,speckle,0.02); %给图像添加乘性噪声Y1=wiener2(J1,[5 5]); %维纳滤波Y2=wiener2(J2,[5 5]);Y3=wiener2(J3,[5 5]);subplot(2,2,1),imshow(x),title(灰度图);subplot(2,2,2),imshow(Y1),title(高斯噪声维纳滤波);subplot(2,2,3),imshow(Y2),title(椒盐噪声维纳滤波);subplot(2,2,4),imshow(Y3),title(乘性噪声维纳滤波);中值滤波I=imread(h:\img.png); x=rgb2gray(I);J1=imnoise(x,gaussian,0,0.02); %给图像添加高斯噪声J2=imnoise(x,salt pepper,0.02);%给图像添加椒盐噪声J3=imnoise(x,speckle,0.02); %给图像添加乘性噪声Y1=medfilt2(J1);%在默认3×3的邻域窗中进行中值滤波Y2=medfilt2(J2);%在默认3×3的邻域窗中进行中值滤波Y3=medfilt2(J3);%在默认3×3的邻域窗中进行中值滤波subplot(2,2,1),imshow(x),title(灰度图);subplot(2,2,2),imshow(Y1),title(高斯噪声中值滤波);subplot(2,2,3),imshow(Y2),title(椒盐噪声中值滤波);subplot(2,2,4),imshow(Y3),title(乘性噪声中值滤波);低通滤波器在频率域实现低通滤波I=imread(h:\img.png); I=rgb2gray(I); figure(1),imshow(I); title(