A Shearlets-Based Method for Rain Removal from Single Images
Source abstract
Abstract
This work focuses on the problem of rain removal from a single image. The directional multilevel system, Shearlets, is used to describe the intrinsic directional and structure sparse priors of rain streaks and the background layer. In this paper, a Shearlets-based convex rain removal model is proposed, which involves three sparse regularizers: including the sparse regularizer of rain streaks and two sparse regularizers of the Shearlets transform of background layer in the rain drops’ direction and the Shearlets transform of rain streaks in the perpendicular direction. The split Bregman algorithm is utilized to solve the proposed convex optimization model, which ensures the global optimal solution. Comparison tests with three state-of-the-art methods are implemented on synthetic and real rainy images, which suggests that the proposed method is efficient both in rain removal and details preservation of the background layer.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Image Enhancement Techniques · Image and Signal Denoising Methods · Advanced Image Fusion Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
Engineering School, DEIM, University of Tuscia, 01100 Viterbo, Italy
Funding
Fostect
References (33)
Show source-provided references
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