Rain removal using single image based on non-negative matrix factorization

Pin Hsian Liu, Chih Yang Lin, Chia Hung Yeh, Li Wei Kang, Kyle Shih Huang Lo, Tai Hwei Hwang, Chia Chen Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Rain streak in an image can degrade the human vision, as well as the image's quality. However, the rain removal of a single image is a challenging problem, because the rain is moving fast and may become torrential. In this paper, a single image rain removal process based on the non-negative matrix factorization is proposed. In the proposed method, the rain image is decomposed into a low-frequency part and a high-frequency part by a Gaussian filter. Therefore, the rain component, which is usually in the middle frequency, could be discarded in high and low frequency domains. In this paper, the non-negative matrix factorization (NMF) method is applied to deal with the rain streak in the low frequency; while in the high frequency part, the concept of Canny edge detection and block copy strategy are utilized separately to remove the rain hidden in high frequency and improve the image quality. By comparing with the state-of-the-art approaches, our proposed method does not need the extra image database to train the desirable dictionary, but still reaches similar results.

Original languageEnglish
Title of host publicationIntelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014
EditorsWilliam Cheng-Chung Chu, Han-Chieh Chao, Stephen Jenn-Hwa Yang
PublisherIOS Press BV
Number of pages10
ISBN (Electronic)9781614994831
StatePublished - 2015
EventInternational Computer Symposium, ICS 2014 - Taichung, Taiwan
Duration: 12 Dec 201414 Dec 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


ConferenceInternational Computer Symposium, ICS 2014


  • Canny edge detection
  • connected component based rain removal
  • non-negative matrix factorization (NMF)
  • rain removal


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