Robust remove noise using multiple degraded images

Ruihua Liu; Fang Li

Robust remove noise using multiple degraded images

Ruihua Liu^*
, Fang Li

^*此作品的通讯作者

数学科学学院

East China Normal University
Chongqing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

2 引用（Scopus）

摘要

In this paper, we propose a model to remove noise or deblurring by multiple degraded images. In the algorithm, we introduce robust L¹ norm data fidelity term and bilateral total variation regularization term. Experimental results show that our algorithm is effective.

源语言	英语
页（从-至）	305-308
页数	4
期刊	Chinese Journal of Electronics
卷	17
期	2
出版状态	已出版 - 4月 2008

其它文件与链接

链接到 Scopus 的出版物

引用此

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title = "Robust remove noise using multiple degraded images",

abstract = "In this paper, we propose a model to remove noise or deblurring by multiple degraded images. In the algorithm, we introduce robust L1 norm data fidelity term and bilateral total variation regularization term. Experimental results show that our algorithm is effective.",

keywords = "Bilateral total variation, Deblurring, Degraded images, Denoising",

author = "Ruihua Liu and Fang Li",

year = "2008",

month = apr,

language = "英语",

volume = "17",

pages = "305--308",

journal = "Chinese Journal of Electronics",

issn = "1022-4653",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "2",

}

TY - JOUR

T1 - Robust remove noise using multiple degraded images

AU - Liu, Ruihua

AU - Li, Fang

PY - 2008/4

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N2 - In this paper, we propose a model to remove noise or deblurring by multiple degraded images. In the algorithm, we introduce robust L1 norm data fidelity term and bilateral total variation regularization term. Experimental results show that our algorithm is effective.

AB - In this paper, we propose a model to remove noise or deblurring by multiple degraded images. In the algorithm, we introduce robust L1 norm data fidelity term and bilateral total variation regularization term. Experimental results show that our algorithm is effective.

KW - Bilateral total variation

KW - Deblurring

KW - Degraded images

KW - Denoising

UR - https://www.scopus.com/pages/publications/42249098856

M3 - 文章

AN - SCOPUS:42249098856

SN - 1022-4653

VL - 17

SP - 305

EP - 308

JO - Chinese Journal of Electronics

JF - Chinese Journal of Electronics

IS - 2

ER -

Robust remove noise using multiple degraded images

摘要

其它文件与链接

指纹

引用此