Novel approach based on fuzzy theory and order statistics in 2D/3D processing of images/videos employing specific hardware

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

Abstract

An approach in filtering of color videos/images that are corrupted by impulsive or additive noises is justified. The difference of current approach in comparison with existing state-of-the-art techniques consists in use of fuzzy rules selecting high similarity pixels in the vicinity of the central one using existing correlation of different channels for an image in the RGB space as well as correlation in the neighboring frames of a video. Employing this correlation permits better preservation of the features, processing separately the areas with different texture. Numerous simulation experiments have confirmed the superiority of the designed techniques via objective criteria (PSNR, MAE, NCD, SSIM) as well as demonstrating better visual perception quality.

Original languageEnglish
Title of host publicationCHILECON 2015 - 2015 IEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies, Proceedings of IEEE Chilecon 2015
EditorsMario F. Fernandez, Gaston H. Lefranc, Ricardo Perez
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages777-782
Number of pages6
ISBN (Electronic)9781467387569
DOIs
StatePublished - 4 Feb 2016
EventIEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2015 - Santiago, Chile
Duration: 28 Oct 201530 Oct 2015

Publication series

NameCHILECON 2015 - 2015 IEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies, Proceedings of IEEE Chilecon 2015

Conference

ConferenceIEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2015
Country/TerritoryChile
CitySantiago
Period28/10/1530/10/15

Keywords

  • Color Video
  • Denoising
  • Image
  • Similarity

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