【图像增强】自适应亮度对比度调节算法C++

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参考

亮度和对比度调节公式，其中alpha负责对比度，beta负责亮度。

O(x,y) = alpha * I(x,y) + beta

如果想要自动调节亮度和对比度，意味着自动调节 alpha 和 beta
假如想要将最小值变到0，最大值变为255，则计算公式如下。

input range = max(I) - min(I)
wanted output range = 255;
alpha = output range / input range = 255 / ( max(I) - min(I) )
min(O) = alpha * min(I) + beta
beta = -min(I) * alpha

直方图剪枝平移

• 平移 -> 亮度
• 剪枝 -> 重定义直方图的范围

下面的图以供理解

代码实现

这里我增加了两个参数，用以调节亮度最低值和直方图的范围

// clipHistPercent 剪枝（剪去总像素的多少百分比）
// histSize 最后将所有的灰度值归到多大的范围
// lowhist 最小的灰度值
void BrightnessAndContrastAuto(const cv::Mat &src, cv::Mat &dst, float clipHistPercent=0, int histSize = 255, int lowhist = 0)
{
    
    CV_Assert(clipHistPercent >= 0);
    CV_Assert((src.type() == CV_8UC1) || (src.type() == CV_8UC3) || (src.type() == CV_8UC4));
    
    float alpha, beta;
    double minGray = 0, maxGray = 0;
    
    //to calculate grayscale histogram
    cv::Mat gray;
    if (src.type() == CV_8UC1) gray = src;
    else if (src.type() == CV_8UC3) cvtColor(src, gray, CV_BGR2GRAY);
    else if (src.type() == CV_8UC4) cvtColor(src, gray, CV_BGRA2GRAY);
    if (clipHistPercent == 0)
    {
        // keep full available range
        cv::minMaxLoc(gray, &minGray, &maxGray);
    }
    else
    {
        cv::Mat hist; //the grayscale histogram
        
        float range[] = { 0, 256 };
        const float* histRange = { range };
        bool uniform = true;
        bool accumulate = false;
        calcHist(&gray, 1, 0, cv::Mat (), hist, 1, &histSize, &histRange, uniform, accumulate);
        
        // calculate cumulative distribution from the histogram
        std::vector<float> accumulator(histSize);
        accumulator[0] = hist.at<float>(0);
        for (int i = 1; i < histSize; i++)
        {
            accumulator[i] = accumulator[i - 1] + hist.at<float>(i);
        }
        
        // locate points that cuts at required value
        float max = accumulator.back();
        
        int clipHistPercent2;
        clipHistPercent2 = clipHistPercent * (max / 100.0); //make percent as absolute
        clipHistPercent2 /= 2.0; // left and right wings
        // locate left cut
        minGray = 0;
        while (accumulator[minGray] < clipHistPercent2)
            minGray++;
        
        // locate right cut
        maxGray = histSize - 1;
        while (accumulator[maxGray] >= (max - clipHistPercent2))
            maxGray--;
    }
    
    // current range
    float inputRange = maxGray - minGray;
    
    alpha = (histSize - 1) / inputRange;   // alpha expands current range to histsize range
    beta = -minGray * alpha + lowhist;             // beta shifts current range so that minGray will go to 0
    
    // Apply brightness and contrast normalization
    // convertTo operates with saurate_cast
    src.convertTo(dst, -1, alpha, beta);
    
    // restore alpha channel from source
    if (dst.type() == CV_8UC4)
    {
        int from_to[] = { 3, 3};
        cv::mixChannels(&src, 4, &dst,1, from_to, 1);
    }
}