C++实现自适应二值化

二值化每次都要调阈值，很头疼，实现一个不依赖OpenCV库的动态二值化算法很有必要。
测试了
参考文献
论文链接
更详细的算法解释
效果如下:

达到了预期的效果。

主要实现代码记录一下。

void MainWindow::BalancedThresholding()
{
    QImage pos = img;
    QRgb *bin = (QRgb *)pos.scanLine(0);
    QRgb *pixels = (QRgb *)img.scanLine(0);

    QRgb threadw = qRgb(255,255,255);
    QRgb threadb = qRgb(0,0,0);

    int w = img.width();
    int h = img.height();
    int index = 0;
    int count = 0;
    long sum = 0;

    int x1,x2,y1,y2;
    int S = w/8.0;
    int s2 = S/2;
    double T = 0.15;
    unsigned long* integralImg = 0;
    integralImg = (unsigned long*)malloc(w*h*sizeof(unsigned long*));
    
    for(int i =0;i<w;i++)
    {
        sum = 0;
        for(int j=0;j<h;j++)
        {
            index = j*w+i;
            sum += qGray(pixels[index]);
            if(i==0)
                integralImg[index] = sum;
            else
                integralImg[index] = integralImg[index-1] + sum;

        }
    }

    for(int i =0;i<w;i++)
    {
        sum = 0;
        for(int j=0;j<h;j++)
        {
            index = j*w+i;

            x1 = i-s2;
            x2 = i+s2;
            y1 = j-s2;
            y2 = j+s2;
            if(x1<0)x1=0;
            if(x2>=w) x2=w-1;
            if(y1<0) y1=0;
            if(y2>=h) y2 = h-1;

            count = (x2-x1)*(y2-y1);

            sum = integralImg[y2*w+x2] - integralImg[y1*w+x2] - integralImg[y2*w +x1] + integralImg[y1*w+x1];
            if((long)(qGray(pixels[index])*count) < (long)(sum*(1.0-T)))
            {
                bin[index] = threadb;
            }
            else
            {
                bin[index] = threadw;
            }
        }
    }
    free (integralImg);
    ui->labelDest->setPixmap(QPixmap::fromImage(pos));
}

这里使用了自己熟悉的Qt，如果需要跨平台，可以使用stb_img库来读写图片，可以摆脱各种大框架的捆绑。