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Images denoising with feature extraction for patch matching in block matching and 3D filtering

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

Abstract

In this paper, we propose a new method for grey scale image denoising. Our method takes advantage of the fact that the mean of the Gaussian white noise is zero. For every patch in the noisy image, we use a line to divide the image into two regions with equal area, and then take the mean of one of the two regions. We select lines with different slopes in order to extract a number of features. We use these extracted features to match the patches in the noisy image. All other steps in our method are the same as those in the standard BM3D. Our experimental results show that our new method outperforms the standard BM3D for (n∈>120, and they are identical, otherwise.

Original languageEnglish
Title of host publicationIntelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings
PublisherSpringer Verlag
Pages398-406
Number of pages9
ISBN (Print)9783319093321
DOIs
StatePublished - 2014
Event10th International Conference on Intelligent Computing, ICIC 2014 - Taiyuan, China
Duration: 3 Aug 20146 Aug 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8588 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Intelligent Computing, ICIC 2014
Country/TerritoryChina
CityTaiyuan
Period3/08/146/08/14

Keywords

  • Gaussian white noise
  • Image denoising
  • block matching and 3D filtering (BM3D)

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