Low-Light Image Enhancement via Pair of Complementary Gamma Functions by Fusion

被引:19
|
作者
Li, Changli [1 ]
Tang, Shiqiang [1 ]
Yan, Jingwen [2 ]
Zhou, Teng [2 ]
机构
[1] Hohai Univ, Coll Comp & Informat Engn, Adv Signal & Image Proc Learning & Engn Lab, Nanjing 211100, Peoples R China
[2] Shantou Univ, Coll Engn, Shantou 515063, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷 / 08期
基金
中国国家自然科学基金;
关键词
Gamma correction (GC); CRT gamma; pair of complementary gamma functions; low-light image enhancement; image dehazing; underwater image restoration; QUALITY ASSESSMENT; REAL-TIME; RETINEX; MODEL; EQUALIZATION;
D O I
10.1109/ACCESS.2020.3023485
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Enhanced images by the traditional gamma correction (GC) method still have low contrast within high illuminance regions. In order to enhance the visibility in dark regions and simultaneously achieve high contrast in bright regions for low-light images, this paper proposes a novel method via a pair of complementary gamma functions (PCGF) by image fusion. We first define PCGF and then show its outstanding potential for low-light image enhancement by some preliminary experimental results. In order to release its performance and verify its effectiveness, we further design a simple enhancement method for low-light images based on it by an elaborately designed fusion strategy. Two input images for fusion are derived from the enhanced image by PCGF and that by proposed sharpening method, respectively. Experiments show that our proposed method can significantly enhance the detail and improve the contrast of low-light image. The qualitative experiment results show that the proposed method is effective and the comparative quantitative assessment shows that it outperforms other state-of-the-art methods.
引用
收藏
页码:169887 / 169896
页数:10
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