Rician Noise Removal via a Learned Dictionary

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

doi:10.1155/2019/8535206

Rician Noise Removal via a Learned Dictionary

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

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10 Scopus citations

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.

Original language	English (US)
Article number	8535206
Journal	Mathematical Problems in Engineering
Volume	2019
DOIs	https://doi.org/10.1155/2019/8535206
State	Published - 2019

ASJC Scopus subject areas

General Mathematics
General Engineering

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10.1155/2019/8535206

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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",

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AU - Tian, Jiapeng

AU - Shen, Lixin

AU - Jiang, Qingtang

AU - Zeng, Xueying

AU - Zou, Yuru

PY - 2019

Y1 - 2019

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AB - 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.

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Rician Noise Removal via a Learned Dictionary

Abstract

ASJC Scopus subject areas

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