请给我一个基于MATLAB的快速自适应中值滤波器的设计程序

以下是一个基于MATLAB的快速自适应中值滤波器的设计程序：

function output = fast_adaptive_median_filter(input, window_size, max_window_size)
% input: 输入图像
% window_size: 初始窗口大小
% max_window_size: 最大窗口大小
% output: 输出图像

% 获取输入图像的大小
[height, width] = size(input);

% 初始化输出图像
output = zeros(height, width);

% 计算窗口半径
window_radius = floor(window_size / 2);

% 遍历输入图像的每一个像素
for i = 1:height
    for j = 1:width
        % 获取当前像素周围的窗口
        row_min = max(1, i - window_radius);
        row_max = min(height, i + window_radius);
        col_min = max(1, j - window_radius);
        col_max = min(width, j + window_radius);
        window = input(row_min:row_max, col_min:col_max);
        
        % 计算窗口的中值
        window_median = median(window(:));
        
        % 如果当前像素与窗口中值的差值小于等于窗口大小的一半，则取当前像素值
        if abs(input(i, j) - window_median) <= window_radius
            output(i, j) = input(i, j);
        % 否则，增加窗口大小并再次计算中值，直到窗口大小达到最大值
        else
            if window_size < max_window_size
                window_size = window_size + 2;
                window_radius = floor(window_size / 2);
                row_min = max(1, i - window_radius);
                row_max = min(height, i + window_radius);
                col_min = max(1, j - window_radius);
                col_max = min(width, j + window_radius);
                window = input(row_min:row_max, col_min:col_max);
                window_median = median(window(:));
                output(i, j) = window_median;
            else
                output(i, j) = window_median;
            end
        end
    end
end

使用方法：

% 读取图像
input = imread('input_image.jpg');

% 设计自适应中值滤波器
window_size = 3; % 初始窗口大小
max_window_size = 21; % 最大窗口大小
output = fast_adaptive_median_filter(input, window_size, max_window_size);

% 显示原始图像和滤波后的图像
figure;
subplot(1, 2, 1);
imshow(input);
title('Input Image');
subplot(1, 2, 2);
imshow(output);
title('Filtered Image');