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Adaptive trimmed averaging filter for noise removal in color images

  • Silesian University of Technology

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

2 Citations (Scopus)

Abstract

In the paper a novel filtering design intended for the removal of mixed impulsive and Gaussian noise contaminating color images is proposed. The new denoising scheme is based on the concept of the robustified vector median, which determines the center of a cluster of most similar pixels. The filter output is the average of pixels belonging to the cluster and thus it can be treated as an adaptive trimmed averaging filter. The new filtering design is capable of suppressing mixed impulsive and Gaussian noise, while preserving and even enhancing image edges. The experiments revealed that the new noise reduction design outperforms the standard trimmed vector median and other state-of-the-art methods. The simplicity of the proposed filter and its low computational load enables its applications in real time image and video enhancement applications.

Original languageEnglish
Title of host publication10th International Conference on Computer Science and Education, ICCSE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-94
Number of pages6
ISBN (Electronic)9781479965984
DOIs
Publication statusPublished - 9 Sept 2015
Event10th International Conference on Computer Science and Education, ICCSE 2015 - Cambridge, United Kingdom
Duration: 22 Jul 201524 Jul 2015

Publication series

Name10th International Conference on Computer Science and Education, ICCSE 2015

Conference

Conference10th International Conference on Computer Science and Education, ICCSE 2015
Country/TerritoryUnited Kingdom
CityCambridge
Period22/07/1524/07/15

Keywords

  • Color image enhancement
  • mixed Gaussian and impulsive noise reduction
  • noise filtering

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Computer Science Applications
  • Signal Processing
  • Education

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