Signal processing for hyperspectral data

Pramod K. Varshney, Manoj K. Arora, Raghuveer M. Rao

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

Abstract

Hyperspectral data form a data-cube consisting of images of an object collected at several hundred, closely spaced wavelengths. They have been found to be of significant potential benefit in areas such as remote sensing of the Earth, medicine, and non-destructive evaluation. Effective extraction of information from the hyperspectral data cube presents several signal processing challenges, some of them unique to hyperspectral data. The problems involved range from registration and enhancement to development of statistical signal processing algorithms and models for object detection and classification. The focus of this paper is to provide an overview of select processing and modeling techniques for hyperspectral data.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesV1181-V1184
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
ISSN (Print)1520-6149

Other

Other2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
CountryFrance
CityToulouse
Period5/14/065/19/06

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Varshney, P. K., Arora, M. K., & Rao, R. M. (2006). Signal processing for hyperspectral data. In 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings (pp. V1181-V1184). [1661492] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 5).