Document Type
Article
Abstract
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.
Publication Date
1-1-2019
ISSN
1024123X
Publication Title
Mathematical Problems in Engineering
Volume
2019
DOI
10.1155/2019/8535206
Recommended Citation
Lu, Jian; Tian, Jiapeng; Shen, Lixin; Jiang, Qingtang; Zeng, Xueying; and Zou, Yuru, "Rician Noise Removal via a Learned Dictionary" (2019). Mathematics and Statistics Faculty Works. 4.
DOI: https://doi.org/10.1155/2019/8535206
Available at:
https://irl.umsl.edu/mathstats-faculty/4
