Rain streak removal based on non-negative matrix factorization

Chia Hung Yeh, Chih Yang Lin*, Kahlil Muchtar, Pin Hsian Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


A rain streak in an image can degrade visual quality of that image to the human eye. Unfortunately, removing the rain streak from a single image represents a very challenging task. In this paper, a single image rain removal process based on non-negative matrix factorization is proposed. First, the rain image is broken down into a low-frequency and high-frequency part by a Gaussian filter. Therefore, the rain component, which lies mostly in the middle frequency range, can be discarded in high and low frequency domains. Next, non-negative matrix factorization (NMF) method is applied to deal with the rain streak in the low frequency domain. Finally, Canny edge detection and block copy strategy are performed separately to remove the rain component in the high frequency domain to improve image quality. In comparison with state-of-the-art approaches, the proposed method achieves competitive results without the need for an extra image database to train the dictionary.

Original languageEnglish
Pages (from-to)20001-20020
Number of pages20
JournalMultimedia Tools and Applications
Issue number15
Publication statusPublished - 2018 Aug 1


  • Canny edge detection
  • Non-negative matrix factorization (NMF)
  • Rain removal

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


Dive into the research topics of 'Rain streak removal based on non-negative matrix factorization'. Together they form a unique fingerprint.

Cite this