Target detection in hyperspectral images using projection pursuit with interference rejection

Agustin I. Ifarraguerri, Hsuan Ren, Chein I. Chang

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

1 Scopus citations

Abstract

We present a method for the automatic, unsupervised detection of spectrally distinct targets from the background using hyperspectral imaging. The approach is based on the concepts of projection pursuit (PP) and unsupervised orthogonal subspace projection (UOSP). It has the advantage of not requiring any prior knowledge of the scene or the objects' spectral signatures. All information is obtained from the data. First, PP is used to both reduce the data dimensionality and locate potential targets. Then, UOSP suppresses the signatures from undesired objects or interferers that cause false detections when a spectral filter is applied. The result is a set of gray scale images where objects belonging to the same spectral class are enhanced while the background and other undesired objects are suppressed. This method is demonstrated using data from the Hyperspectral Digital Imagery Collection Experiment (HYDICE).

Original languageEnglish
Title of host publicationImage and Signal Processing for Remote Sensing IV
EditorsSebastiano Bruno Serpico
PublisherSPIE
Pages54-62
Number of pages9
ISBN (Electronic)9780819429599
DOIs
StatePublished - 4 Dec 1998
EventImage and Signal Processing for Remote Sensing IV 1998 - Barcelona, Spain
Duration: 21 Sep 199825 Sep 1998

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume3500
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceImage and Signal Processing for Remote Sensing IV 1998
Country/TerritorySpain
CityBarcelona
Period21/09/9825/09/98

Keywords

  • HYDICE
  • Hyperspectral imaging
  • Projection pursuit
  • Target detection
  • Unsupervised orthogonal subspace projection

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