Rain streaks removal from single image based on texture constraint of background scene

被引:3
作者
Du, Shuangli [1 ]
Liu, Yiguang [2 ]
Ye, Mao [3 ]
Zhao, Minghua [1 ]
Li, Zheng [2 ]
机构
[1] Xian Univ Technol, Sch Comp Sci & Engn, Shaanxi Key Lab Network Comp & Secur Technol, Xian, Peoples R China
[2] Sichuan Univ, Coll Comp Sci, Chengdu, Peoples R China
[3] Univ Elect Sci & Technol, Sch Comp Sci & Engn, Chengdu, Peoples R China
关键词
Rain removal; Texture constraint; Gabor filter; Low rank; Split Bregman technique; MODEL;
D O I
10.1016/j.neucom.2020.08.025
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Removing rain streaks from single image is mathematically ill-defined and the known strategies tend to over-smooth the background and remove image details. To tackle this problem, this paper proposes a novel two-stage system. Firstly, in view of the frequency and direction of rain streaks, Gabor filter is first used to suppress rain streaks. Based on the bases extracted from natural images, several Gabor filtered images extracted from the input rain image are fused by a new proposed method, and the fused result provides a texture constraint for the non-rain part. Secondly, a low-rank model is adopted to describe rain streaks as they take on similar and repeated patterns in an imaging scene. By combining the texture constraint and the low-rank model, a global cost function is constructed. Finally, an optimization strategy is proposed based on the split Bregman technique, which solves the function with high performance. A large number of experimental results show the competitive performance and efficiency of the proposed method in comparison with the state-of-the-art methods, making it more applicable in real practices. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:224 / 238
页数:15
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