@article{9b041b679b7a45879fc229eedc6c933c,
title = "Rician Noise Removal via a Learned Dictionary",
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.",
author = "Jian Lu and Jiapeng Tian and Lixin Shen and Qingtang Jiang and Xueying Zeng and Yuru Zou",
note = "Funding Information: The authors would like to thank one of the authors of [32] for providing the source code of CZ method. This work was supported in part by the National Natural Science Foundation of China under Grants 11871348, 61872429, and 61373087, by the Natural Science Foundation of Guangdong, China, under Grants 2015A030313550 and 2015A030313557, by the HD Video R&D Platform for Intelligent Analysis and Processing in Guangdong Engineering Technology Research Centre of Colleges and Universities (no. GCZX-A1409), by Natural Science Foundation of Shenzhen under Grant JCYJ20170818091621856, and by the Guangdong Key Publisher Copyright: {\textcopyright} 2019 Jian Lu et al.",
year = "2019",
doi = "10.1155/2019/8535206",
language = "English (US)",
volume = "2019",
journal = "Mathematical Problems in Engineering",
issn = "1024-123X",
publisher = "Hindawi Publishing Corporation",
}