Gabor-filtering-based probabilistic collaborative representation for hyperspectral image classification

Yan Xu, Qian Du, Wei Li, Nicolas Younan

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

7 Citations (Scopus)

Abstract

This paper presents Gabor-filtering-based probabilistic collaborative representation for hyperspectral image classification. Compared with the original collaborative representation classifier (CRC) and the CRC using Gabor features, the proposed classifier offers superior classification performance. The regularized versions of CRC using Gabor features have excellent classification performance; however, those classifiers have high computational cost. Experimental results show that the proposed approach can generate high classification accuracy with lower computational cost.

Original languageEnglish
Title of host publication2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5081-5084
Number of pages4
ISBN (Electronic)9781538671504
DOIs
Publication statusPublished - 31 Oct 2018
Externally publishedYes
Event38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain
Duration: 22 Jul 201827 Jul 2018

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2018-July

Conference

Conference38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Country/TerritorySpain
CityValencia
Period22/07/1827/07/18

Keywords

  • Classification
  • Collaborative representation
  • Gabor filtering
  • Hyperspectral imagery
  • Probabilistic

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