title: Automatic single-image-based rain streaks removal via image decomposition.
abstract: 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 was rarely studied in the literature, where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by 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. Experimental results demonstrate the efficacy of the proposed algorithm.
authors.affiliation: Institute of Information Science, Academia Sinica, Taipei, Taiwan.
authors.forename: Li-Wei
authors.initials: LW
authors.lastname: Kang
authors.forename: Chia-Wen
authors.initials: CW
authors.lastname: Lin
authors.forename: Yu-Hsiang
authors.initials: YH
authors.lastname: Fu
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D011891:Rain; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique