A spatial/spectral protocol for quality assurance of decompressed hyperspectral data for practical applications

Anna Brook, Eyal Ben-Dor

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

Abstract

A detailed spatial/spectral protocol to test the influence of compressed-decompressed on the hyperspectral image data is presented. The proposed scheme is evaluated by applying an hybrid algorithm (LCT and SPHIT) on AISA-Dual hyperspectral images. For the purpose of reliable thematic results, the preservation and recovering of reflectance spectral features should be on the main concern. Therefore, this protocol contains three stages of data processing: radiance, radiometric/spectral preprocessed radiance, and atmospheric corrected reflectance (generated from radiometric/spectral preprocessed radiance). As for impact on exploitation, we consider IsoData classification, anomaly-detection, and spectral indices as benchmark applications. Additionally, the proposed scheme is compared with common validation approaches, such as spectral response assessment and anomaly-detection techniques.

Original languageEnglish
Title of host publication2nd Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2010 - Workshop Program
Pages1-4
DOIs
StatePublished - 2010
Externally publishedYes
Event2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Reykjavik, Iceland
Duration: 14 Jun 201016 Jun 2010

Publication series

Name2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program

Conference

Conference2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010
Country/TerritoryIceland
CityReykjavik
Period14/06/1016/06/10

Keywords

  • Hyperspectral data compression
  • Quality assurance
  • Spatial/Spectral analysis

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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