Python实现特定场景去除高光算法详解

算法思路

1、求取源图I的平均灰度，并记录rows和cols；

2、按照一定大小，分为N*M个方块，求出每块的平均值，得到子块的亮度矩阵D；

3、用矩阵D的每个元素减去源图的平均灰度，得到子块的亮度差值矩阵E；

4、通过插值算法，将矩阵E差值成与源图一样大小的亮度分布矩阵R；

5、得到矫正后的图像result=I-R；

应用场景

光照不均匀的整体色泽一样的物体，比如工业零件，ocr场景。

代码实现

import cv2
import numpy as np

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
   img = cv2.imread(file)
   b,g,r = cv2.split(img)
   dstb = unevenLightCompensate(b, blockSize)
   dstg = unevenLightCompensate(g, blockSize)
   dstr = unevenLightCompensate(r, blockSize)
   dst = cv2.merge([dstb, dstg, dstr])
   result = np.concatenate([img, dst], axis=1)
cv2.imwrite('result.jpg', result)

实验效果

补充

OpenCV实现光照去除效果

1.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;
}

实现效果

2.方法二

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;
}

实现效果

来源：https://blog.csdn.net/qq_14845119/article/details/122193134