Hyperspectral change detection using IR-MAD and feature reduction

Prashanth Marpu, Paolo Gamba, Jon A. Benediktsson

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

Abstract

A method for change detection between two hyperspectral datasets is presented. The iteratively reweighted multivariate alteration detection (IR-MAD) method is used for change detection. The strong changes are first eliminated based on the principal component analysis (PCA) of the difference image and IR-MAD is applied on the datasets after feature reduction with the PCA of the original bands. The method is demonstrated on a bitemporal hyperspectral dataset. The results show good correlation with ground truth.

Original languageEnglish
Title of host publication2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings
Pages98-101
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Vancouver, BC, Canada
Duration: 24 Jul 201129 Jul 2011

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011
Country/TerritoryCanada
CityVancouver, BC
Period24/07/1129/07/11

Other keywords

  • IR-MAD
  • PCA
  • change detection
  • hyperspectral

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