Video deraining and desnowing using temporal correlation and low-rank matrix completion

Jin Hwan Kim, Jae Young Sim, Chang-Su Kim

Research output: Contribution to journalArticlepeer-review

200 Citations (Scopus)


A novel algorithm to remove rain or snow streaks from a video sequence using temporal correlation and low-rank matrix completion is proposed in this paper. Based on the observation that rain streaks are too small and move too fast to affect the optical flow estimation between consecutive frames, we obtain an initial rain map by subtracting temporally warped frames from a current frame. Then, we decompose the initial rain map into basis vectors based on the sparse representation, and classify those basis vectors into rain streak ones and outliers with a support vector machine. We then refine the rain map by excluding the outliers. Finally, we remove the detected rain streaks by employing a low-rank matrix completion technique. Furthermore, we extend the proposed algorithm to stereo video deraining. Experimental results demonstrate that the proposed algorithm detects and removes rain or snow streaks efficiently, outperforming conventional algorithms.

Original languageEnglish
Article numberA9
Pages (from-to)2658-2670
Number of pages13
JournalIEEE Transactions on Image Processing
Issue number9
Publication statusPublished - 2015 Sept 1

Bibliographical note

Publisher Copyright:
© 1992-2012 IEEE.


  • Desnowing
  • Low rank matrix completion and sparse representation
  • Rain streak removal
  • Video deraining

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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