matlab CLAHE代码

下面是一个基于Matlab的CLAHE（对比度受限的自适应直方图均衡化）代码示例：

function output = clahe(input, clipLimit, tileSize)
% CLAHE (Contrast Limited Adaptive Histogram Equalization)
% input: 输入图像
% clipLimit: 对比度限制因子
% tileSize: 均衡化时划分的块大小
% output: 均衡化后的输出图像

% 处理输入参数
if nargin < 2
    clipLimit = 0.01;
end
if nargin < 3
    tileSize = [8 8];
end

% 将输入图像转换为灰度图像
if size(input, 3) == 3
    input = rgb2gray(input);
end

% 计算图像的行数和列数
[height, width] = size(input);

% 计算每个块的大小
numTilesX = ceil(width / tileSize(2));
numTilesY = ceil(height / tileSize(1));
tileWidth = floor(width / numTilesX);
tileHeight = floor(height / numTilesY);

% 计算每个块的直方图
histograms = zeros(256, numTilesX * numTilesY);
for i = 1:numTilesY
    for j = 1:numTilesX
        x = (j - 1) * tileWidth + 1;
        y = (i - 1) * tileHeight + 1;
        tile = input(y:min(y+tileHeight-1, height), x:min(x+tileWidth-1, width));
        tileHist = imhist(tile);
        histograms(:, (i-1)*numTilesX+j) = tileHist;
    end
end

% 计算裁剪限制
clipLimit = round(clipLimit * tileWidth * tileHeight);

% 对每个块进行均衡化
output = zeros(height, width);
for i = 1:numTilesY
    for j = 1:numTilesX
        x = (j - 1) * tileWidth + 1;
        y = (i - 1) * tileHeight + 1;
        tile = input(y:min(y+tileHeight-1, height), x:min(x+tileWidth-1, width));
        tileHist = histograms(:, (i-1)*numTilesX+j);
        tileHist(tileHist > clipLimit) = clipLimit;
        tileHist = tileHist / sum(tileHist);
        tileHist = cumsum(tileHist);
        tileHist = round(tileHist * 255);
        tileHist = max(tileHist, 1);
        tileEq = tileHist(double(tile) + 1);
        output(y:min(y+tileHeight-1, height), x:min(x+tileWidth-1, width)) = tileEq;
    end
end

% 将输出图像转换为uint8格式
output = uint8(output);
end

这个函数实现了CLAHE算法，它将输入图像分成多个小块，对每个小块进行直方图均衡化，然后将块重新组合成输出图像。CLAHE算法还引入了对比度限制因子，用于控制块内像素的对比度，避免过度增强噪声。