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author:

Wu, HanQing (Wu, HanQing.) [1] | You Sheng, Xia (You Sheng, Xia.) [2] (Scholars:夏又生)

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EI Scopus

Abstract:

Many practical applications need to eliminate noise from noisy images. This paper first introduce a simplified support vector regression (SSVR) method for single image denoising under mixture noise environments. The proposed SSVR method has a lower computational complexity than related SVR approaches to image denoising. Furthermore, we propose a novel multiple SVR approach for multi-image denoising by extending the SSVR method. Experiment results show that the proposed SVR-based approach has good performance in fast removing mixture noise. © 2011 IEEE.

Keyword:

Image denoising Mixtures

Community:

  • [ 1 ] [Wu, HanQing]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 2 ] [You Sheng, Xia]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

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Year: 2011

Volume: 1

Page: 47-51

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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