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Low-complexity lossless compression of hyperspectral imagery via adaptive filtering

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dc.contributor.author Klimesh, Matthew A.
dc.date.accessioned 2007-11-30T22:49:21Z
dc.date.available 2007-11-30T22:49:21Z
dc.date.issued 2005-09-13
dc.identifier.citation Consultative Committee for Space Data Systems (CCSDS) Area and Working Group Meeting, Data Compression Working Group, Atlanta, Georgia, September 13-15, 2005 en
dc.identifier.clearanceno 05-2522
dc.identifier.uri http://hdl.handle.net/2014/40561
dc.description.abstract A low-complexity, adaptive predictive technique for lossless compression of hyperspectral data is presented. The technique relies on the sign algorithm from the repertoire of adaptive filtering. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity. en
dc.description.sponsorship NASA/JPL en
dc.format.extent 589690 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2006. en
dc.subject lossless data compression en
dc.subject hyperspectral image compression en
dc.title Low-complexity lossless compression of hyperspectral imagery via adaptive filtering en
dc.type Preprint en


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