帮我写一段对图像进行非局部均值去噪的matlab代码
时间: 2023-12-04 16:02:30 浏览: 83
基于matlab使用非局部均值滤波nlm算法实现图像去噪
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好的,以下是一个简单的 MATLAB 代码示例,实现了非局部均值去噪:
```matlab
function [out] = NLMdenoise(img, patch_size, window_size, h)
% img: 输入图像
% patch_size: 图像块大小
% window_size: 搜索窗口大小
% h: 平滑参数
% 将图像转换为 double 类型
img = im2double(img);
% 计算图像块的半径
patch_radius = floor(patch_size/2);
% 计算搜索窗口的半径
window_radius = floor(window_size/2);
% 复制输入图像,以便在图像边缘应用非局部均值去噪
img_padded = padarray(img,[window_radius+patch_radius,window_radius+patch_radius],'symmetric');
% 初始化输出图像
out = zeros(size(img));
% 遍历所有像素
for i = 1:size(img,1)
for j = 1:size(img,2)
% 计算当前图像块的位置
patch_row_start = i;
patch_row_end = i + patch_size - 1;
patch_col_start = j;
patch_col_end = j + patch_size - 1;
% 获取当前图像块
patch = img_padded(patch_row_start:patch_row_end, patch_col_start:patch_col_end);
% 初始化权重和像素值
weight_total = 0;
pixel_total = 0;
% 遍历搜索窗口内的所有像素
for m = i-window_radius:i+window_radius
for n = j-window_radius:j+window_radius
% 计算当前搜索窗口内的图像块的位置
window_row_start = m;
window_row_end = m + patch_size - 1;
window_col_start = n;
window_col_end = n + patch_size - 1;
% 获取当前搜索窗口内的图像块
window_patch = img_padded(window_row_start:window_row_end, window_col_start:window_col_end);
% 计算当前图像块和搜索窗口内的图像块之间的欧氏距离
diff = patch - window_patch;
distance = sum(diff(:).^2);
% 计算权重
weight = exp(-distance/h^2);
% 累加像素值和权重
pixel_total = pixel_total + window_patch * weight;
weight_total = weight_total + weight;
end
end
% 计算平均像素值
out(i,j) = pixel_total/weight_total;
end
end
end
```
要使用这个函数,只需将图像、图像块大小、搜索窗口大小和平滑参数传递给函数即可。例如,要对名为 "img.png" 的图像进行非局部均值去噪,可以使用以下代码:
```matlab
img = imread('img.png');
patch_size = 7;
window_size = 21;
h = 0.1;
out = NLMdenoise(img, patch_size, window_size, h);
imshow(out);
```
请注意,此代码仅用于演示目的,可能需要根据您的应用场景进行修改和优化。
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