Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2420
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dc.contributor.authorMahapatra, D K-
dc.contributor.authorRoy, L P-
dc.date.accessioned2016-01-01T05:17:31Z-
dc.date.available2016-01-01T05:17:31Z-
dc.date.issued2015-12-
dc.identifier.citation12th Annual IEEE India Conference (INDICON 2015), Jamia Nagar, New Delhi, 17-20 Dec 2015en_US
dc.identifier.urihttp://hdl.handle.net/2080/2420-
dc.descriptionCopyright for this paper belongs to proceeding publisheren_US
dc.description.abstractIn the context of synthetic aperture radar (SAR) data analysis, formulation of accurate models for clutter statistics is a crucial task. In this paper, compound-Gaussian distribution with inverse gamma texture (IΓ-CG), is presented for multilook SAR amplitude data. An estimator based on method of logcumulants (MoLC), which stems from the adoption of second kind statistics and Mellin transform is developed for estimating its parameters. The IΓ-CG model is validated by using multilook synthetic data and single look real clutter data of amplitude SAR images. Experimental results show that the IΓ-CG model outmatches the state-of-the-art pdfs that clearly demonstrates the applicability of the model.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectClutteren_US
dc.subjectCompound-Gaussian modelen_US
dc.subjectSynthetic aperture radar (SAR) imageen_US
dc.subjectMethod of log-cumulantsen_US
dc.subjectMellin transformen_US
dc.titleAn Estimator for Compound-Gaussian Multilook SAR Clutter Amplitude with Inverse Gamma Textureen_US
dc.typeArticleen_US
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