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SAR image compression

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dc.contributor.authorSakarya, FA
dc.contributor.authorEmek, S
dc.date.accessioned2026-06-27T12:56:26Z
dc.date.issued1997
dc.description.abstractClassical image compression algorithms such as Discrete Cosine Transform (DCT) [1], Karhunen-Loeve Transform (KLT) [1], and Subband Decomposition using Wavelet Filters (SDWF) [2,3] are well-understood for optical imaging. However, their applications to synthetic aperture radar (SAR) images have not been well-studied. This paper applies DCT, KLT and SDWF to raw SAR images after appropriate preprocessing, and compares the results based on three performance criteria, namely energy gain (E-C), transform coding gain (G(T)), and peak-to-peak signal-to-noise ratio (PSNR).en
dc.description.urihttps://doi.org/10.1109/acssc.1996.599066
dc.identifier.doi10.1109/acssc.1996.599066
dc.identifier.endpage862
dc.identifier.isbn0-8186-7646-9
dc.identifier.issn1058-6393
dc.identifier.startpage858
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47920
dc.identifier.wosA1997BH95W00171
dc.language.isoeng
dc.publisherI E E E, COMPUTER SOC PRESS
dc.relation.conference30th Asilomar Conference on Signals, Systems and Computers
dc.relation.ispartofTHIRTIETH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2
dc.subjectComputer Science
dc.subjectEngineering
dc.titleSAR image compression
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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