Rician Noise Removal via a Learned Dictionary

Jian Lu, Jiapeng Tian, Lixin Shen, Qingtang Jiang, Xueying Zeng, Yuru Zou

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


This paper proposes a new effective model for denoising images with Rician noise. The sparse representations of images have been shown to be efficient approaches for image processing. Inspired by this, we learn a dictionary from the noisy image and then combine the MAP model with it for Rician noise removal. For solving the proposed model, the primal-dual algorithm is applied and its convergence is studied. The computational results show that the proposed method is promising in restoring images with Rician noise.

Original languageEnglish (US)
Article number8535206
JournalMathematical Problems in Engineering
StatePublished - 2019

ASJC Scopus subject areas

  • General Mathematics
  • General Engineering


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