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author:

Xia, Youshen (Xia, Youshen.) [1] | Deng, Zhipo (Deng, Zhipo.) [2] | Zheng, Wei Xing (Zheng, Wei Xing.) [3]

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EI

Abstract:

In this paper, we analyze a novel algorithm for 2-D ARMA model parameter estimation in the presence of noise and then develop a fast and efficient blind image restoration algorithm. We show that the novel algorithm can minimize a quadratic convex optimization problem and has a lower computational complexity than the conventional algorithms. As a result, the novel algorithm involves no convergence and local minimum issue. Moreover, the proposed blind image restoration algorithm can overcome the local minimization problem. Computed results confirm that the novel algorithm can more quickly obtain more accurate estimates than the conventional algorithms in the presence of noise. © 2013 Elsevier Ltd. All rights reserved.

Keyword:

Convex optimization Image reconstruction Parameter estimation Random processes Restoration

Community:

  • [ 1 ] [Xia, Youshen]College of Mathematics and Computer Science, Fuzhou University, China
  • [ 2 ] [Deng, Zhipo]College of Mathematics and Computer Science, Fuzhou University, China
  • [ 3 ] [Zheng, Wei Xing]School of Computing, Engineering and Mathematics, University of Western Sydney, Sydney, Australia

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Source :

Automatica

ISSN: 0005-1098

Year: 2013

Issue: 10

Volume: 49

Page: 3056-3064

3 . 1 3 2

JCR@2013

4 . 8 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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