Single-frame-based rain removal via image decomposition

Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image has been rarely studied in the literature, where no temporal information among successive images can be exploited, making it more challenging. In this paper, to the best of our knowledge, we are among the first to propose a single-frame-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis (MCA). Instead of directly applying conventional image decomposition technique, we first decompose an image into the low-frequency and highfrequency parts using a bilateral filter. The high-frequency part is then decomposed into “rain component” and “nonrain component” via performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Exper...

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Yu-Hsiang Fu, Li-Wei Kang, Chia-Wen Lin, Chiou-Ting Hsu
• Keywords: ICASSP 2011, Image, Image Decomposition, Rain Removal, Signal Processing