removeHaze.py

import cv2
import numpy as np
import copy

def removeHaze(HazeImg, Transmission, A, delta):
    '''
    :param HazeImg: Hazy input image
    :param Transmission: estimated transmission
    :param A: estimated airlight
    :param delta: fineTuning parameter for dehazing --> default = 0.85
    :return: result --> Dehazed image
    '''

    # This function will implement equation(3) in the paper
    # " https://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Meng_Efficient_Image_Dehazing_2013_ICCV_paper.pdf "

    epsilon = 0.0001
    Transmission = pow(np.maximum(abs(Transmission), epsilon), delta)

    HazeCorrectedImage = copy.deepcopy(HazeImg)
    if(len(HazeImg.shape) == 3):
        for ch in range(len(HazeImg.shape)):
            temp = ((HazeImg[:, :, ch].astype(float) - A[ch]) / Transmission) + A[ch]
            temp = np.maximum(np.minimum(temp, 255), 0)
            HazeCorrectedImage[:, :, ch] = temp
    else:
        temp = ((HazeImg.astype(float) - A[0]) / Transmission) + A[0]
        temp = np.maximum(np.minimum(temp, 255), 0)
        HazeCorrectedImage = temp
    return(HazeCorrectedImage)