Retinex算法在低可见度照片的应用

Question

本人目前在学习大数据算法，在应用Retinex算法遇到很多问题，希望找到一个Retinex算法的完整版代码，通过算法实现暗光下照片增强，让照片从模糊到清晰

Answer 1

该回答引用ChatGPT GPT-4

运行结果

代码如下

import cv2
import numpy as np

def single_scale_retinex(img, sigma):
    retinex = np.log10(img) - np.log10(cv2.GaussianBlur(img, (0, 0), sigma))
    return retinex

def multi_scale_retinex(img, sigma_list):
    retinex = np.zeros_like(img)
    for sigma in sigma_list:
        retinex += single_scale_retinex(img, sigma)
    retinex = retinex / len(sigma_list)
    return retinex

def color_restoration(img, alpha, beta):
    img_sum = np.sum(img, axis=2, keepdims=True)
    color_restoration = beta * (np.log10(alpha * img) - np.log10(img_sum))
    return color_restoration

def retinex_process(img, sigma_list, G, b, alpha, beta):
    img = np.float64(img) + 1.0
    img_retinex = multi_scale_retinex(img, sigma_list)
    img_color = color_restoration(img, alpha, beta)
    img_retinex = G * (img_retinex * img_color + b)

    for i in range(img_retinex.shape[2]):
        img_retinex[:, :, i] = np.clip(img_retinex[:, :, i], 0, 255)
    img_retinex = np.uint8(img_retinex)

    return img_retinex

def main():
    img = cv2.imread('1.jpg')

    sigma_list = [15, 80, 250]
    G = 5.0
    b = 25.0
    alpha = 125.0
    beta = 46.0

    img_retinex = retinex_process(img, sigma_list, G, b, alpha, beta)

    cv2.imshow('1', img)
    cv2.imshow('Retinex', img_retinex)
    cv2.waitKey(0)

if __name__ == "__main__":
    main()