이미지 디포깅 기술의 포그 복구 문제

import numpy as np
import cv2

def dark_channel(img, patch_size):
  min_channel = np.min(img, axis=2)
  return cv2.erode(min_channel, np.ones((patch_size, patch_size)))

def atmospheric_light(img, dark_img, top_percentage):
  h, w = img.shape[:2]
  flattened_img = img.reshape(h*w, 3)
  flattened_dark = dark_img.flatten()
  top_num = int(h*w*top_percentage)
  indices = np.argpartition(flattened_dark, -top_num)[-top_num:]
  top_pixels = flattened_img[indices]
  atmospheric_light = np.max(top_pixels, axis=0)
  return atmospheric_light

def transmission_map(img, atmosphere_light, omega, patch_size):
  img_normalized = img / atmosphere_light
  dark = dark_channel(img_normalized, patch_size)
  transmission = 1 - omega * dark
  return transmission

def recover(img, transmission, atmosphere_light, omega):
  transmission_normalized = np.maximum(transmission, omega)
  recover = (img - atmosphere_light) / transmission_normalized + atmosphere_light
  return np.clip(recover, 0, 255).astype(np.uint8)

def dehaze(img, omega=0.95, patch_size=15, top_percentage=0.001):
  dark = dark_channel(img, patch_size)
  atmospheric_light = atmospheric_light(img, dark, top_percentage)
  transmission = transmission_map(img, atmospheric_light, omega, patch_size)
  output = recover(img, transmission, atmospheric_light, omega)
  return output

if __name__ == '__main__':
  img = cv2.imread('hazy_image.jpg')
  output = dehaze(img)
  cv2.imwrite('dehazed_image.jpg', output)