常用去噪之均值滤波

 均值滤波是用像素点邻域的均值代替该像素点，通过将各个像素点做平均平滑滤波，平滑效果与滤波窗口有关，窗口越大，平滑效果越强，但细节和边缘也越加模糊。

matlab实现

%均值滤波  test
A = imread('E:\test\Lenna.jpg');
B = imnoise(A,'gaussian');

figure;subplot(221),imshow(A);title('原图')
subplot(222),imshow(B);title('高斯噪声图')

C = m_average_filter(B,5);
subplot(223),imshow(uint8(C));title('均值滤波后')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Purpose: do averge filter
% Author: pottor
% Date: 2017/5/10

function out = m_average_filter(in,w)

if( mod(w,2)==0 )
    error( 'w must be odd' );
end

out = in;
hw = floor(w/2);

F = ones(w,w)/(w*w);

if size(in,3) == 1
    [m,n] = size(in);
    for i = 1:m
        for j = 1:n
            iMin = max(i-hw,1);
            iMax = min(i+hw,m);
            jMin = max(j-hw,1);
            jMax = min(j+hw,n);

            I = in(iMin:iMax,jMin:jMax);
            out(i,j) = sum(sum(double(I).*F((iMin:iMax)-i+hw+1,(jMin:jMax)-j+hw+1)));
        end
    end
else
    r = in(:,:,1);
    g = in(:,:,2);
    b = in(:,:,3);
    [m,n] = size(r);
    for i = 1:m
        for j = 1:n
            iMin = max(i-hw,1);
            iMax = min(i+hw,m);
            jMin = max(j-hw,1);
            jMax = min(j+hw,n);

            Ir = r(iMin:iMax,jMin:jMax);
            Ig = g(iMin:iMax,jMin:jMax);
            Ib = b(iMin:iMax,jMin:jMax);

            out(i,j,1) = sum(sum(double(Ir).*F((iMin:iMax)-i+hw+1,(jMin:jMax)-j+hw+1)));
            out(i,j,2) = sum(sum(double(Ig).*F((iMin:iMax)-i+hw+1,(jMin:jMax)-j+hw+1)));
            out(i,j,3) = sum(sum(double(Ib).*F((iMin:iMax)-i+hw+1,(jMin:jMax)-j+hw+1)));
        end
    end
end

滤波效果