Detection of group of stationary targets using high-resolution SAR and EO images

So Yeon Kim, Donghwan Cha, Sang Wan Kim

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

3 Scopus citations

Abstract

In this study, the target detection is performed using TerraSAR-X and WorldView-2 high-resolution satellite images, considering the characteristics of targets. The target of our interest is characterized by being stationary and appearing as cluster targets. After the target detection of SAR image based on CFAR (Constant False Alarm Rate) algorithm, a series of processing (target pixel clustering, network clustering and coherence analysis) is performed in order to reduce false alarms. However, the false alarm is still too quite large to narrow down the candidate areas. The fast and effective ellipse detection using hough transform is developed and applied to an EO (Electro Optical) image. The result helps us to lower significantly the false alarm. Based on the detected ellipse and network analysis the candidates of cluster targets are successfully identified with very low false alarm.

Original languageEnglish
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1769-1772
Number of pages4
ISBN (Electronic)9781479957750
DOIs
StatePublished - 4 Nov 2014
EventJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 - Quebec City, Canada
Duration: 13 Jul 201418 Jul 2014

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

ConferenceJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014
Country/TerritoryCanada
CityQuebec City
Period13/07/1418/07/14

Keywords

  • Electro Optical (EO)
  • high-resolution
  • image fusion
  • Synthetic Aperture Radar (SAR)
  • Target detection

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