Local normalization in OpenCV

Question

I\'m trying to implement in OpenCV a local normalization algorithm to reduce the difference of illumination in an image. I have found a MATLAB function, and I have implement

Answer 1

Here is my implementation (I am using sigma1=2, sigma2=20):

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
using namespace cv;

int main(int argc, char** argv)
{
    Mat img, gray, float_gray, blur, num, den;

    // Load color image
    img = cv::imread("lena.png", 1);
    if( !img.data ) {
        return -1;
    }

    // convert to grayscale
    cv::cvtColor(img, gray, CV_BGR2GRAY);

    // convert to floating-point image
    gray.convertTo(float_gray, CV_32F, 1.0/255.0);

    // numerator = img - gauss_blur(img)
    cv::GaussianBlur(float_gray, blur, Size(0,0), 2, 2);
    num = float_gray - blur;

    // denominator = sqrt(gauss_blur(img^2))
    cv::GaussianBlur(num.mul(num), blur, Size(0,0), 20, 20);
    cv::pow(blur, 0.5, den);

    // output = numerator / denominator
    gray = num / den;

    // normalize output into [0,1]
    cv::normalize(gray, gray, 0.0, 1.0, NORM_MINMAX, -1);

    // Display
    namedWindow("demo", CV_WINDOW_AUTOSIZE );
    imshow("demo", gray);

    waitKey(0);

    return 0;
}

The result as expected:

Note that you can specify the kernel size as Size(0,0) and it will be computed from the sigma values.

Answer 2

you need to normalize the image between 0 and 255 before converting it to CV_8UC1

Answer 3

This is the Python implementation of the same algo above:

import cv2
import numpy as np

img = cv2.imread('/home/anmol/Downloads/lena.png')

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

float_gray = gray.astype(np.float32) / 255.0

blur = cv2.GaussianBlur(float_gray, (0, 0), sigmaX=2, sigmaY=2)
num = float_gray - blur

blur = cv2.GaussianBlur(num*num, (0, 0), sigmaX=20, sigmaY=20)
den = cv2.pow(blur, 0.5)

gray = num / den

gray = cv2.normalize(gray, dst=gray, alpha=0.0, beta=1.0, norm_type=cv2.NORM_MINMAX)

cv2.imwrite("./debug.png", gray * 255)

Outout: