Color facial image denoising based on rpca and noisy pixel detection

Zhaojun Yuan, Xudong Xie, Xiaolong Ma, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

In this paper, a novel approach for color facial-image denoising based on robust principal component analysis (RPCA) [1] in the L*a*b* color space and noisy pixel detection is proposed. Firstly, RPCA is employed for color facial-image recovery in the L*a*b* space. Then, the reconstructed image is used for noisy pixel detection. Finally, the denoised facial-image can be obtained. Experiments are conducted based on the AR database, where our proposed method is compared with several state-of-the-art image-denoising methods. Experimental results show that our method can achieve a better performance in terms of both quantitatively evaluation and visual quality.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages2449-2453
Number of pages5
DOIs
Publication statusPublished - 18 Oct 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 26 May 201331 May 2013

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period26/05/1331/05/13

Keywords

  • color facial-image
  • Image denoising
  • noisy pixel detection
  • RPCA

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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