Python实现特定场景去除高光算法

1、

def unevenLightCompensate(gray, blockSize):
    #gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    average = np.mean(gray)
    rows_new = int(np.ceil(gray.shape[0] / blockSize))
    cols_new = int(np.ceil(gray.shape[1] / blockSize))
    blockImage = np.zeros((rows_new, cols_new), dtype=np.float32)
    for r in range(rows_new):
        for c in range(cols_new):
            rowmin = r * blockSize
            rowmax = (r + 1) * blockSize
            if (rowmax > gray.shape[0]):
                rowmax = gray.shape[0]
            colmin = c * blockSize
            colmax = (c + 1) * blockSize
            if (colmax > gray.shape[1]):
                colmax = gray.shape[1]
            imageROI = gray[rowmin:rowmax, colmin:colmax]
            temaver = np.mean(imageROI)
    
            blockImage[r, c] = temaver
    
    
    
    blockImage = blockImage - average
    blockImage2 = cv2.resize(blockImage, (gray.shape[1], gray.shape[0]), interpolation=cv2.INTER_CUBIC)
    gray2 = gray.astype(np.float32)
    dst = gray2 - blockImage2
    dst[dst>255]=255
    dst[dst<0]=0
    dst = dst.astype(np.uint8)
    dst = cv2.GaussianBlur(dst, (3, 3), 0)
    #dst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
    return dst


if __name__ == '__main__':
    file = 'www.png'
    blockSize = 8
    im01 = cv2.imread(file)
    b_img,g_img,r_img = cv2.split(im01)
    dstb_img_img = unevenLightCompensate(b_img, blockSize)
    dstg_img = unevenLightCompensate(g_img, blockSize)
    dstr_img = unevenLightCompensate(r_img, blockSize)
    im02 = cv2.merge([dstb_img, dstg_img, dstr_img])
    result = np.concatenate([im01, im02], axis=1)
cv2.imwrite('result.jpg', result)
    

 

 

 

2、方法一(RGB归一化)

int main(int argc, char *argv[])
{
    //double temp = 255 / log(256);
    //cout << "doubledouble temp ="<< temp<<endl;
     
    Mat  image = imread("D://vvoo//sun_face.jpg", 1);
    if (!image.data)
    {
        cout << "image loading error" <<endl;
        return -1;
    }
    imshow("原图", image);
    Mat src(image.size(), CV_32FC3);
    for (int i = 0; i < image.rows; i++)
    {
        for (int j = 0; j < image.cols; j++)
        {
            src.at<Vec3f>(i, j)[0] = 255 * (float)image.at<Vec3b>(i, j)[0] / ((float)image.at<Vec3b>(i, j)[0] + (float)image.at<Vec3b>(i, j)[2] + (float)image.at<Vec3b>(i, j)[1]+0.01);
            src.at<Vec3f>(i, j)[1] = 255 * (float)image.at<Vec3b>(i, j)[1] / ((float)image.at<Vec3b>(i, j)[0] + (float)image.at<Vec3b>(i, j)[2] + (float)image.at<Vec3b>(i, j)[1]+0.01);
            src.at<Vec3f>(i, j)[2] = 255 * (float)image.at<Vec3b>(i, j)[2] / ((float)image.at<Vec3b>(i, j)[0] + (float)image.at<Vec3b>(i, j)[2] + (float)image.at<Vec3b>(i, j)[1]+0.01);
        }
    }
     
    normalize(src, src, 0, 255, CV_MINMAX);
       
    convertScaleAbs(src,src);
    imshow("rgb", src);
    imwrite("C://Users//TOPSUN//Desktop//123.jpg", src);
    waitKey(0);
    return 0;
}

 

 

3、

void unevenLightCompensate(Mat &image, int blockSize)
{
    if (image.channels() == 3) cvtColor(image, image, 7);
    double average = mean(image)[0];
    int rows_new = ceil(double(image.rows) / double(blockSize));
    int cols_new = ceil(double(image.cols) / double(blockSize));
    Mat blockImage;
    blockImage = Mat::zeros(rows_new, cols_new, CV_32FC1);
    for (int i = 0; i < rows_new; i++)
    {
        for (int j = 0; j < cols_new; j++)
        {
            int rowmin = i*blockSize;
            int rowmax = (i + 1)*blockSize;
            if (rowmax > image.rows) rowmax = image.rows;
            int colmin = j*blockSize;
            int colmax = (j + 1)*blockSize;
            if (colmax > image.cols) colmax = image.cols;
            Mat imageROI = image(Range(rowmin, rowmax), Range(colmin, colmax));
            double temaver = mean(imageROI)[0];
            blockImage.at<float>(i, j) = temaver;
        }
    }
    blockImage = blockImage - average;
    Mat blockImage2;
    resize(blockImage, blockImage2, image.size(), (0, 0), (0, 0), INTER_CUBIC);
    Mat image2;
    image.convertTo(image2, CV_32FC1);
    Mat dst = image2 - blockImage2;
    dst.convertTo(image, CV_8UC1);
}
int main(int argc, char *argv[])
{
    //double temp = 255 / log(256);
    //cout << "doubledouble temp ="<< temp<<endl;
     
    Mat  image = imread("C://Users//TOPSUN//Desktop//2.jpg", 1);
    if (!image.data)
    {
        cout << "image loading error" <<endl;
        return -1;
    }
    imshow("原图", image);
    unevenLightCompensate(image, 12);
    imshow("rgb", image);
    imwrite("C://Users//TOPSUN//Desktop//123.jpg", image);
    waitKey(0);
    return 0;
}

 

 

 

 

 

 

参考：https://www.zhuxianfei.com/python/56327.html

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标签：gray,高光,Python,blockSize,image,float,int,去除,new
来源： https://www.cnblogs.com/herd/p/16340902.html