An automatic K-Wishart distribution ship detector for PolSAR data

Weiwei Fan, Feng Zhou, Mingliang Tao, Xueru Bai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper presents an automatic ship detection algorithm for polarimetric synthetic aperture radar (PolSAR) data. Based on the non-Gaussian K-Wishart distribution model for complex backscattering coefficients, the PolSAR image is clustered automatically by a modified expectation maximization algorithm. A goodness-of-fit test is incorporated to improve the model fitness of the cluster iteratively. Then, the SPAN of ship cluster center is used to detect ships. Finally, the experimental results of a real measured UAVSAR dataset show that the proposed algorithm could improve the ability of weak target detection while reduces the rate of false alarm and miss detections.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4738-4741
Number of pages4
ISBN (Electronic)9781509033324
DOIs
StatePublished - 1 Nov 2016
Externally publishedYes
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • Goodness-of-fit test
  • K-Wishart classifier
  • polarimetric synthetic aperture radar (PolSAR)
  • ship detection

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