Joint feature based rain detection and removal from videos

Xinwei Xue, Xin Jin, Chenyuan Zhang, Satoshi Goto

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Adverse weather, such as rain or snow, can cause difficulties in the processing of video streams. Because the appearance of raindrops can affect the performance of human tracking and reduce the efficiency of video compression, the detection and removal of rain is a challenging problem in outdoor surveillance systems. In this paper, we propose a new algorithm for rain detection and removal based on both spatial and wavelet domain features. Our system involves fewer frames during detection and removal, and is robust to moving objects in the rain. Experimental results demonstrate that the proposed algorithm outperforms existing approaches in terms of subjective and objective quality.

Original languageEnglish
Pages (from-to)1195-1203
Number of pages9
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number6
Publication statusPublished - 2013 Jun


  • Bilateral filtering
  • DWT (discrete wavelet transform)
  • Rain detection
  • Rain removal

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Signal Processing


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