计算实例
close all clear clc figure('Number','off'); f = imread('lena.bmp'); subplot(231);imshow(f);title('lena彩色原图'); g = rgb2gray(f); subplot(234);imshow(g),title('lena灰度原图'); n = imnoise(g,'salt & pepper',0.01); %n = imnoise(g,'gaussian',0,0.01); %n = imnoise(g,'poisson'); subplot(232);imshow(n),title('噪声图像'); m1 = medfilt2(n,[5 5]); subplot(235);imshow(m1),title('5*5中值滤波'); m2 = medfilt2(n,[5 1]); subplot(233);imshow(m2);title('5*1中值滤波'); m3 = medfilt2(n,[1 5]); subplot(236);imshow(m3);title('组合滤波器'); [imPSNR(n,g),imPSNR(m1,g),imPSNR(m3,g),imPSNR(g,g); imKBlur(n,g),imKBlur(m1,g),imKBlur(m3,g),imKBlur(g,g)]
PSNR峰值信噪比
function [ PSNR ] = imPSNR( J , I ) %imPSNR Summary of this function goes here % I is a image with high quality % J is a image with noise % the function will return the PSNR of the noise image width = size(I,2); heigh = size(I,1); if( width ~= size(J,2) || heigh ~= size(J,1) ) disp('Please check the input image have the same size'); return end K = (I-J).*(I-J); PSNR = sum(sum(K,1)); PSNR = PSNR / (width * heigh); PSNR=10*log10(255*255/PSNR); end
KBlur模糊系数
function [ KBlur ] = imKBlur( J , I ) w = [-1 1; 1 -1]; J = imfilter(J,w); I = imfilter(I,w); Sin = sum(sum(I,1)); Sout = sum(sum(J,1)); KBlur = Sout/Sin; end