Blind color image deconvolution based on wavelet decomposition

Yu He, Kim Hui Yap, Li Chen, Lap Pui Chau

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

Abstract

This paper presents a new framework to address blind color image deconvolution based on wavelet decomposition. Blind color image deconvolution is a challenging problem due to the lack of information available. Conventional methods based on single-input single-output (SISO) model experience significant color artifacts in the restored images. On the other hand, there are limitations on the practicality of using multi-input multi-output (MEMO) model in solving this problem as the color channels are usually highly correlated. In view of this, this paper proposes a new framework to solve blind color image deconvolution by first decomposing the color channels into wavelet subbands, and performing image deconvolution using a combination of SISO and single-input multi-output (SIMO) models. Experimental results show that the proposed method is able to achieve satisfactory restored images.

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing 2005, ICIP 2005
PublisherIEEE Computer Society
Pages763-766
Number of pages4
ISBN (Print)0780391349, 9780780391345
DOIs
Publication statusPublished - Sept 2005
Externally publishedYes
EventIEEE International Conference on Image Processing 2005, ICIP 2005 - Genova, Italy
Duration: 11 Sept 200514 Sept 2005

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing 2005, ICIP 2005
Country/TerritoryItaly
CityGenova
Period11/09/0514/09/05

Keywords

  • Blind color image deconvolution
  • Conjugate gradient optimization
  • SISO and SIMO models
  • Wavelet decomposition

ASJC Scopus subject areas

  • General Engineering

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