Compressive sensing-based image denoising using adaptive multiple sampling and optimal error tolerance

Wonseok Kang, Eunsung Lee, Eunjung Chea, Aggelos K Katsaggelos, Joonki Paik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we present a compressive sensing-based image denoising algorithm using spatially adaptive image representation and estimation of optimal error tolerance based on sparse signal analysis. The proposed method performs block-based multiple compressive sampling after decomposing the sparse signal into feature and non-feature regions using simple statistical analysis. For minimization of recovery error and number of iterations, the modified OMP method estimates the optimal error tolerance using the average variance in the recovery step. Experimental results demonstrate that the proposed denoising algorithm better removes noise without undesired artifacts than existing state-of-the-art methods in terms of both objective (PSNR/SSIM) and subjective measures. Processing time of the proposed method is 5 to 10 times faster than the standard OMP-based method.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages2503-2507
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

Keywords

  • Compressed sensing
  • image denoising
  • matching pursuit algorithms

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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