Efficient blind image restoration based on 1-D generalized cross validation

Pak Kong Lun, Tommy C L Chan, T. C. Hsung, David D. Feng

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

Abstract

Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. The generalized cross validation (GCV) approach was proposed to solve the problem and it has shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data size and long computational time of the approach are undesirable even with the current computing machines. h this paper, an efficient algorithm is proposed for blind image restoration. For this approach, the original 2-D blind image restoration problem is converted into 1-D ones by using the discrete periodic Radon transform, 1-D GCV algorithm is then applied hence the memory size and computational time required are greatly reduced. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.
Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings
PublisherSpringer Verlag
Pages434-441
Number of pages8
ISBN (Print)3540426809, 9783540426806
Publication statusPublished - 1 Jan 2001
Event2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001 - Beijing, China
Duration: 24 Oct 200126 Oct 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2195
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001
CountryChina
CityBeijing
Period24/10/0126/10/01

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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