CIDER: Corrected inverse-denoising filter for image restoration

You Wei Wen*, Kwok Po NG, Wai Ki Ching

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

In this paper we propose and develop a new algorithm, Corrected Inverse-Denoising filtER (CIDER) to restore blurred and noisy images. The approach is motivated by a recent algorithm ForWaRD, which uses a regularized inverse filter followed by a wavelet denoising scheme. In ForWaRD, the restored image obtained by the regularized inverse filter is a biased estimate of the original image. In CIDER, the correction term is added to this restored image such that the resulting one is an unbiased estimator. Similarly, the wavelet denoising scheme can be applied to suppress the residual noise. Experimental results show that the performance of CIDER is better than other existing methods in our comparison study.

Original languageEnglish
Title of host publicationEnergy Minimization Methods in Computer Vision and Pattern Recognition - 6th International Conference, EMMCVPR, 2007 Proceedings
PublisherSpringer Verlag
Pages112-126
Number of pages15
ISBN (Print)9783540741954
DOIs
Publication statusPublished - 2007
Event6th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2007 - Ezhou, China
Duration: 27 Aug 200729 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4679 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2007
Country/TerritoryChina
CityEzhou
Period27/08/0729/08/07

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Inverse filter
  • Regularization
  • Restoration
  • Wavelet denoising

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