Persistent Link:
http://hdl.handle.net/10150/608744
Title:
HYPERSPECTRAL IMAGE COMPRESSION
Author:
Hallidy, William H., Jr.; Doerr, Michael
Affiliation:
Systems & Processes Engineering Corporation
Issue Date:
1999-10
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
Systems & Processes Engineering Corporation (SPEC) compared compression and decompression algorithms and developed optimal forms of lossless and lossy compression for hyperspectral data. We examined the relationship between compression-induced distortion and additive noise, determined the effect of errors on the compressed data, and showed that the data could separate targets from clutter after more than 50:1 compression.
Keywords:
Compression; Rice; Wavelet; Hyperspectral; Target/Clutter; Bit Error
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleHYPERSPECTRAL IMAGE COMPRESSIONen_US
dc.contributor.authorHallidy, William H., Jr.en
dc.contributor.authorDoerr, Michaelen
dc.contributor.departmentSystems & Processes Engineering Corporationen
dc.date.issued1999-10en
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractSystems & Processes Engineering Corporation (SPEC) compared compression and decompression algorithms and developed optimal forms of lossless and lossy compression for hyperspectral data. We examined the relationship between compression-induced distortion and additive noise, determined the effect of errors on the compressed data, and showed that the data could separate targets from clutter after more than 50:1 compression.en
dc.subjectCompressionen
dc.subjectRiceen
dc.subjectWaveleten
dc.subjectHyperspectralen
dc.subjectTarget/Clutteren
dc.subjectBit Erroren
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/608744en
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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