一种基于U-Net生成对抗网络的低照度图像增强方法

doi:10.3969/j.issn.0372-2112.2020.02.005

电子学报 ›› 2020, Vol. 48 ›› Issue (2): 258-264.DOI: 10.3969/j.issn.0372-2112.2020.02.005

一种基于U-Net生成对抗网络的低照度图像增强方法

江泽涛, 覃露露

桂林电子科技大学广西图像图形处理与智能处理重点实验室, 广西桂林 541004

收稿日期:2019-04-03 修回日期:2019-08-10 出版日期:2020-02-25
- 作者简介:
- 江泽涛 男.1961年3月出生,江西九江人.桂林电子科技大学教授,博士生导师,主要从事图像处理、计算机视觉、信息安全方面的研究;覃露露 女.1993年7月出生,广西百色人.桂林电子科技大学硕士研究生,主要从事图像增强、图像理解方面的研究.E-mail:luluqin766@qq.com
- 基金资助:
- 国家自然科学基金 (No.61572147，No.61876049，No.61762066）; 广西科技计划 (No.AC16380108）; 广西图像图形智能处理重点实验项目 (No.GIIP201701，No.GIIP201801，No.GIIP201802，No.GIIP201803）; 广西研究生教育创新计划 (No.YCBZ2018052，No.2019YCXS043）

Low-Light Image Enhancement Method Based on U-Net Generative Adversarial Network

JIANG Ze-tao, QIN Lu-lu

The Key Laboratory of Image and Graphic Intelligent Processing in Guangxi, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China

Received:2019-04-03 Revised:2019-08-10 Online:2020-02-25 Published:2020-02-25

摘要/Abstract

摘要： 在低照度环境下采集的图像具有低信噪比、低对比度及低分辨率等特点，导致图像难以识别利用.为了提升低照度图像的质量，本文提出一种基于U-Net生成对抗网络的低照度图像增强方法.首先利用U-Net框架实现生成对抗网络中的生成网络，然后利用该生成对抗网络学习从低照度图像到正常照度图像的特征映射，最终实现低照度图像的照度增强.实验结果表明，与主流算法相比，本文提出的方法能够更有效的提升低照度图像的亮度与对比度.

关键词: 低照度图像, 图像增强, 生成对抗网络, 深度学习

Abstract: The images acquired in the low illumination environment have the characteristics of low signal-to-noise ratio, low contrast and low resolution, which make the image difficult to identify and utilize.In order to improve the image quality of low-light images, this paper proposes a low-light image enhancement method based on U-net generative adversarial network (GAN).First, the U-net framework is used to implement the generative network of GAN, and then the GAN is used to learn the feature mapping from the low-light image to the normal-light image, and ultimately achieve illumination enhancement for the low-light image.Finally, this method is verified by experiments.The experimental results show that, compared with the mainstream algorithm, the proposed algorithm can effectively improve the brightness and contrast of low-light image.

Key words: low-light image, image enhancement, generative adversarial network(GAN), deep learning

中图分类号:

TP391

江泽涛, 覃露露. 一种基于U-Net生成对抗网络的低照度图像增强方法[J]. 电子学报, 2020, 48(2): 258-264.

JIANG Ze-tao, QIN Lu-lu. Low-Light Image Enhancement Method Based on U-Net Generative Adversarial Network[J]. Acta Electronica Sinica, 2020, 48(2): 258-264.

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一种基于U-Net生成对抗网络的低照度图像增强方法

Low-Light Image Enhancement Method Based on U-Net Generative Adversarial Network

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