Two-stage Rain Image Removal Based on Density Guidance

被引：0

作者：

Mei, Tiancan ^{[1
]}

Cao, Min ^{[1
]}

Yang, Hong ^{[2
]}

Gao, Zhi ^{[3
]}

Yi, Guohong ^{[4
]}

机构：

[1] Wuhan Univ, Sch Elect Informat, Wuhan 430072, Peoples R China

[2] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100190, Peoples R China

[3] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430072, Peoples R China

[4] Wuhan Inst Technol, Sch Comp Sci & Engn, Wuhan 430205, Peoples R China

来源：

JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY | 2023年 / 45卷 / 04期

关键词：

Image deraining; Physics model; cGAN; Density-aware; Gated fusion; MODEL;

D O I：

10.11999/JEIT220157

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

As the most common severe weather, rain can degrade the performance of many vision systems designed for clear imaging conditions. In order to realize the simultaneous removal of rain streaks and rain accumulation, and to deal with various real rain scenes, a two-stage rain image restoration method guided by rain density classification is proposed, which integrates physics model and cGAN refinement. Extensive experiments are conducted on representative synthetic rain datasets and realrain scenes. Quantitative and qualitative results demonstrate the superiority of the proposed method in terms of effectiveness and generalization ability.

引用

页码：1383 / 1390

页数：8