方法一:filter2
clear all;
I=imread('lena.bmp');
%读入预处理图像
imshow(I)
%显示预处理图像
K1=filter2(fspecial('average',3),I)/255;
%进行3*3均值滤波
K2=filter2(fspecial('average',5),I)/255;
%进行5*5均值滤波
K3=filter2(fspecial('average',7),I)/255;
%进行7*7均值滤波
figure,imshow(K1)
figure,imshow(K2)
figure,imshow(K3)
方法二:双循环语句,移动平均法
%均值滤波
clc,clear;
f=imread('lena.bmp');
subplot(121),imshow(f),title('原正瞎春图');
f1=imnoise(f,'gaussian',0.002,0.0008);
%subplot(222),imshow(f1),title('添加举耐高斯噪声图');
k1=floor(3/2)+1;
k2=floor(3/2)+1;
X=f1;
[M,N]=size(X);
uint8 Y=zeros(M,N);
funBox=zeros(3,3);
for i=1:M-3
for j=1:N-3
funBox=X(i:i+3,j:j+3);
s=sum(funBox(:));
h=s/9;
Y(i+k1,j+k2)=h;
神悉 end;
end;
Y=Y/255;
subplot(122),imshow(Y),title('均值滤波');
实现图: