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A Statistical Analysis for Wavelength-Resolution SAR Image Stacks
Fed Univ Pampa UNIPAMPA, BRA.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312x
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
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2020 (English)In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 17, no 2, p. 227-231Article in journal (Refereed) Published
Abstract [en]

This letter presents a clutter statistical analysis for stacks of wavelength-resolution synthetic aperture radar (SAR) images. Each image stack consists of SAR images generated by the same sensor, using the same flight track illuminating the same scene but with a time separation between the illuminations. We test three candidate statistical distributions for time changes in the stack, namely, Rician, Rayleigh, and log-normal. The tests results reveal that the Rician distribution is a very good candidate for modeling stack of wavelength-resolution SAR images, where 98.59 & x0025; of the tested samples passed the Anderson-Darling (AD) goodness-of-fit test. Also, it is observed that the presence of changes in the ground scene is related to the tested samples that have failed in the AD test for the Rician distribution hypothesis.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2020. Vol. 17, no 2, p. 227-231
Keywords [en]
Synthetic aperture radar, Radar polarimetry, Image resolution, Data models, Statistical analysis, Rician channels, Geometry, Anderson-Darling (AD) test, CARABAS II, change detection, image stack, multitemporal synthetic aperture radar (SAR) images, SAR
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Remote Sensing
Identifiers
URN: urn:nbn:se:bth-19226DOI: 10.1109/LGRS.2019.2917627ISI: 000510900300009OAI: oai:DiVA.org:bth-19226DiVA, id: diva2:1394903
Available from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-20Bibliographically approved

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Palm, BrnaPettersson, MatsVu, Viet Thuy

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