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Removing Rain Streaks by a Linear Model

IEEE access, 2020, Vol.8, p.54802-54815 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2020.2981643 ;CODEN: IAECCG

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  • Title:
    Removing Rain Streaks by a Linear Model
  • Author: Wang, Yinglong ; Liu, Shuaicheng ; Xie, Dehua ; Zeng, Bing
  • Subjects: Color imagery ; Cost function ; Image color analysis ; Image sequences ; Imaging ; Machine vision ; Pixels ; Rain ; rain detection ; Rain removal ; rain???s approximation ; rain???s linear model ; Shape ; Videos ; Vision systems
  • Is Part Of: IEEE access, 2020, Vol.8, p.54802-54815
  • Description: Removing rain streaks from a single image continues to draw attentions today in outdoor vision systems. In this paper, we present an efficient method to remove rain streaks. First, the location map of rain pixels needs to be known as precisely as possible, to which we implement a relatively accurate detection of rain streaks by utilizing two characteristics of rain streaks.The key component of our method is to represent the intensity of each detected rain pixel using a linear model: p=\alpha s + \beta , where p is the observed intensity of a rain pixel and s represents the intensity of the background (i.e., before rain-affected). To solve \alpha and \beta for each detected rain pixel, we concentrate on a window centered around it and form an L_{2} -norm cost function by considering all detected rain pixels within the window, where the corresponding rain-removed intensity of each detected rain pixel is estimated by some neighboring non-rain pixels. By minimizing this cost function, we determine \alpha and \beta so as to construct the final rain-removed pixel intensity. Compared with several state-of-the-art works, our proposed method can remove rain streaks from a single color image much more efficiently - it offers not only a better visual quality but also a speed-up of several times to one degree of magnitude compared to other conventional deraining methods.
  • Publisher: Piscataway: IEEE
  • Language: English
  • Identifier: ISSN: 2169-3536
    EISSN: 2169-3536
    DOI: 10.1109/ACCESS.2020.2981643
    CODEN: IAECCG
  • Source: Directory of Open Access Journals
    IEEE Xplore Open Access Journals
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