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Robust Trilateral Filtering with Reachability-Based Impulse Detection for Mixed Noise Removal

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

Abstract

In this paper, a new color image denoising filter is proposed with the goal of efficiently eliminating mixed noise consisting of Gaussian and impulsive noise. The new approach builds upon the trilateral filtering concept by introducing a sophisticated impulse detection strategy founded on a generalized reachability notion and an enhanced Rank-Ordered Absolute Differences similarity metric. In order to enhance the accuracy of impulse detection even more, in a preprocessing stage, a bilateral filter is employed to suppress Gaussian noise without hindering structural details. Experimental evaluation on benchmark test images reveals that the presented technique performs better than state-of-The-Art techniques as far as denoising quality is concerned.

Original languageEnglish
Title of host publicationICRAMI 2025 - 2025 International Conference on Recent Advances in Mathematics and Informatics
EditorsChaouki Aouiti, Patnaik Srikanta, Khaled Berrah, Hakim Bendjenna, Abdallah Meraoumia, Mohamed Gasmi
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331563875
DOIs
Publication statusPublished - 2025
EventInternational Conference on Recent Advances in Mathematics and Informatics, ICRAMI 2025 - Sousse, Tunisia
Duration: 20 Nov 202523 Nov 2025

Publication series

NameICRAMI 2025 - 2025 International Conference on Recent Advances in Mathematics and Informatics

Conference

ConferenceInternational Conference on Recent Advances in Mathematics and Informatics, ICRAMI 2025
Country/TerritoryTunisia
CitySousse
Period20/11/2523/11/25

Keywords

  • gaussian noise
  • image denoising
  • impulsive noise
  • impulsive noise
  • mixed noise
  • robust filter
  • trilateral filter

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Mathematics (miscellaneous)
  • Analysis
  • Computational Mathematics

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