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Improving K-SVD denoising by post-processing its method-noise

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Various patch-based image denoising algorithms have been shown to be very effective. Nevertheless, in most cases the difference between the noisy image and its denoised version (called 'method-noise') still contains traces of the original image content. In this paper we propose a novel technique for improving the K-SVD denoising results. Our scheme starts by applying the K-SVD on the given noisy image. Then, for each patch, we recover the 'stolen' image content information from the method-noise by performing iterations of de-noising using the same atoms that represent the first-stage de-noised patch. Experimental results demonstrate the efficiency of this technique.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Pages435-439
Number of pages5
DOIs
StatePublished - 2013
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: 15 Sep 201318 Sep 2013

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period15/09/1318/09/13

Keywords

  • Image denoising
  • K-SVD
  • dictionary
  • method-noise
  • sparse representations

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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