Hyperspectral image classification using Fisher criterion-based Gabor cube selection and multi-task joint sparse representation

Sen Jia, Yao Xie, Linlin Shen, Lin Deng

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

1 Citation (Scopus)

Abstract

Recently, Gabor wavelet transformation has been introduced for feature extraction of hyperspectral imagery. Due to the discriminative power of obtained Gabor features, high classification performance has been achieved. However, thousands of Gabor features cause too much burden for onboard computation, limiting the efficiency of the method. In fact, not all features have a positive effect on classification. In this paper, we have proposed a Gabor cube selection-based Multi-task Joint Sparse Representation framework, abbreviated as MT-SG, for hyperspectral imagery classification. Firstly, based on the Fisher discrimination criterion, the most representative Gabor cubes for each class have been picked out. Next, under multi-task joint sparse representation framework, a coefficient vector can be obtained for each test sample with the selected cube features, which can be applied for the following residual-based classification. Experimental results on real hyperspectral data have demonstrated the feasibility and efficiency of the proposed method.

Original languageEnglish
Title of host publication2015 7th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2015
PublisherIEEE Computer Society
ISBN (Electronic)9781467390156
DOIs
Publication statusPublished - 2 Jul 2015
Externally publishedYes
Event7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2015 - Tokyo, Japan
Duration: 2 Jun 20155 Jun 2015

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume2015-June
ISSN (Print)2158-6276

Conference

Conference7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2015
Country/TerritoryJapan
CityTokyo
Period2/06/155/06/15

Keywords

  • Gabor wavelet
  • Hyperspectral imagery
  • multi-task joint sparse representation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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