Automated display of hyperspectral images with unsupervised segmentation

Sangwook Lee, Jonghwa Lee, Chulhee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we investigate automated display methods for hyperspectral images with unsupervised segmentation. First, we apply an unsupervised segmentation method, which will produce a number of unlabeled classes. Then, we choose the classes whose sizes are larger than a threshold value. Then, we apply a feature extraction method to the chosen classes and find dominant discriminant features, which are used to display the hyperspectral images. We also exploit the use of the principal component analysis for the display of hyperspectral images. Experimental images show that the color images produced by the proposed methods show interesting characteristics compared to the conventional pseudo-color image.

Original languageEnglish
Title of host publicationSatellite Data Compression, Communication, and Processing V
DOIs
Publication statusPublished - 2009
EventSatellite Data Compression, Communication, and Processing V - San Diego, CA, United States
Duration: 2009 Aug 42009 Aug 5

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7455
ISSN (Print)0277-786X

Other

OtherSatellite Data Compression, Communication, and Processing V
CountryUnited States
CitySan Diego, CA
Period09/8/409/8/5

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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