Image denoising based on contourlet-domain HMT models using cycle spinning

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2 Scopus citations

Abstract

We propose a new method for image denoising based on contourlet-domain hidden Markov tree (CHMT) models, which have been recently introduced. CHMT models achieve superior denoising results over wavelet-domain HMT (WHMT) models in terms of visual quality. But denoising by means of CHMT still introduces some artifacts due to the lack of translation invariance of the contourlet transform. We employ a cycle-spinning-based technique to develop translation invariant CHMT denoising scheme. This scheme achieves enhanced estimation results for images that are corrupted with additive Gaussian noise. Our experiments show that the proposed approach outperforms both WHMT-based denoising method and CHMT-based denoising method, in both visual quality and the PSNR values.

Original languageEnglish
Title of host publicationProceedings - International Conference on Computer Science and Software Engineering, CSSE 2008
Pages162-165
Number of pages4
DOIs
StatePublished - 2008
EventInternational Conference on Computer Science and Software Engineering, CSSE 2008 - Wuhan, Hubei, China
Duration: 12 Dec 200814 Dec 2008

Publication series

NameProceedings - International Conference on Computer Science and Software Engineering, CSSE 2008
Volume6

Conference

ConferenceInternational Conference on Computer Science and Software Engineering, CSSE 2008
Country/TerritoryChina
CityWuhan, Hubei
Period12/12/0814/12/08

Keywords

  • Contuorlet
  • Cycle spinning
  • Denoising
  • HMT

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