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101 0 $aeng
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181   $ctxt
182   $cc
183   $acr
200 10$a2008 IEEE Southwest Symposium on Image Analysis and Interpretation
210 31$a[Place of publication not identified]$cI E E E$d2008
215   $a1 online resource (xvi, 241 pages)
300   $aBibliographic Level Mode of Issuance: Monograph
311 08$a9781424422968 
311 08$a1424422965 
330   $aImage noise often hinders the analysis and understanding of most remote sensing imagery. Synthetic aperture radar (SAR) images, in particular, suffer from a phenomenon known as speckle. Speckle is the result of the coherent sum of scattering mechanisms within a resolution cell and is typically modeled as multiplicative noise. Numerous approaches have been taken to reduce speckle, the most promising of which are adaptive and statistically based. These algorithms typically take advantage of the statistics of speckle or the multi-scale image structure to detect regions of similarity. Several of these algorithms also take advantage of the multi-channel nature of polarimetric SAR to improve the region detection. This work presents two enhancements to such an algorithm with an application toward polarimetric parameter estimation and change detection and presents results using the Japanese satellite-based Phased Array L-band Synthetic Aperture Radar (PALSAR) system.
606   $aImage analysis$vCongresses
615  0$aImage analysis
676   $a621.367
702   $aIEEE Staff
801  0$bPQKB
906   $aPROCEEDING
912   $a9910145112903321
996   $a2008 IEEE Southwest Symposium on Image Analysis and Interpretation$92399049
997   $aUNINA