7X7的双边滤波matlab代码

下面是一个7x7的双边滤波的MATLAB代码示例：

% 读取图像
img = imread('lena.jpg');

% 双边滤波参数
sigma_r = 50;  % 范围标准差
sigma_d = 10;  % 像素距离标准差

% 图像双边滤波
filtered_img = bilateral_filter(img, 7, sigma_r, sigma_d);

% 显示结果
subplot(1,2,1), imshow(img), title('原始图像');
subplot(1,2,2), imshow(filtered_img), title('双边滤波后图像');

% 双边滤波函数
function [filtered_img] = bilateral_filter(img, window_size, sigma_r, sigma_d)
    % 填充边缘
    img = padarray(img, [floor(window_size/2) floor(window_size/2)], 'symmetric');
    [m, n] = size(img);
    filtered_img = zeros(m, n);

    % 计算距离权重矩阵
    [X,Y] = meshgrid(-floor(window_size/2):floor(window_size/2), -floor(window_size/2):floor(window_size/2));
    G = exp(-(X.^2+Y.^2)/(2*sigma_d^2));
    for i = 1+floor(window_size/2):m-floor(window_size/2)
        for j = 1+floor(window_size/2):n-floor(window_size/2)
            % 取出窗口
            window = img(i-floor(window_size/2):i+floor(window_size/2), j-floor(window_size/2):j+floor(window_size/2));
            % 计算强度权重矩阵
            H = exp(-(window-img(i,j)).^2/(2*sigma_r^2));
            % 计算双边滤波结果
            filtered_img(i,j) = sum(sum(H.*G.*window))/sum(sum(H.*G));
        end
    end
    % 去除边缘填充
    filtered_img = filtered_img(1+floor(window_size/2):m-floor(window_size/2), 1+floor(window_size/2):n-floor(window_size/2));
end

在上面的代码中，我们首先读取一个图像，并设置双边滤波参数。然后，我们调用一个名为“bilateral_filter”的函数，该函数将图像作为输入，以及窗口大小、范围标准差和像素距离标准差。该函数使用两个高斯权重矩阵来计算像素之间的权重，然后根据这些权重计算出每个像素的双边滤波结果。最后，我们显示原始图像和双边滤波后的图像。