网上的介绍太多了，但绝大多数Matlab代码应用了较多的循环，速度较慢。本代码充分应用矩阵运算，循环次数少，速度极快。

归一化到0到1之间以后，加入零均值，标准差为0.01的高斯白噪声，得到下图

设置${\sigma }_s=5，{\sigma }_r=0.2$，邻域边长$k=9，$得到滤波效果

笔记本CPU为i7-4710HQ，0.1秒，灰度图滤波速度很快，RGB彩色图即进行三次灰度图滤波，耗时乘3。

代码：

clear all
close all
f = imread('滤波原始图.jpg');
[row, col, depth] = size(f);
f = double(f);
f = imnoise(f / 255, 'gaussian', 0, 0.01);
figure, imshow(f);
%% 双边滤波
sigma_s = 5;
sigma_r = 0.2;
tic
result = zeros(row, col, depth);
k = 9;
radius = floor(k / 2);
f_padded = padarray(f, [radius radius], 'symmetric');
for l = 1 : depth
	A_sum = zeros(row, col);
    for i = -radius : radius
        for j = -radius : radius
            moving_f = f_padded(i + radius + 1 : end + i - radius, j + radius + 1 : end + j - radius, l);
            A = exp(-(i ^ 2 + j ^ 2) / (2 * sigma_s ^ 2) - (moving_f - f(:, :, l) .^ 2 / (2 * sigma_r ^ 2)));
            result(:, :, l) = result(:, :, l) + moving_f .* A;
            A_sum = A_sum + A;
        end
    end
    result(:, :, l) = result(:, :, l) ./ A_sum;
end
result = result * 255;
result = uint8(result);
toc;
figure, imshow(result);