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Object Detection with Few Training Data: Detection of Subsiding Troughs in SAR Interferograms

  • Paweł RotterEmail author
  • Jacek Strzelczyk
  • Stanisława Porzycka-Strzelczyk
  • Claudio Feijoo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10245)

Abstract

Subsiding troughs that are the result of mining activities can be detected in SAR interferograms as approximately elliptic shapes against the noisy background. Despite large areas being covered by interferogram, the number of positive samples, which can be used for automatic learning, is limited. In this paper we propose two alternative methods for the detection of subsiding troughs: the first one is designed to detect any circular shapes and does not require any learning set and the second is based on automatic learning but requires a reduced number of positive samples. The two proposed methods can support manual inspection of large areas in SAR interferograms.

Keywords

Subsiding troughs SAR interferograms Gabor filter 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Paweł Rotter
    • 1
    Email author
  • Jacek Strzelczyk
    • 2
  • Stanisława Porzycka-Strzelczyk
    • 2
  • Claudio Feijoo
    • 3
    • 4
  1. 1.Department of Automatics and Biomedical EngineeringAGH-University of Science and TechnologyKrakówPoland
  2. 2.Department of Geoinformatics and Applied Computer ScienceAGH-University of Science and TechnologyKrakówPoland
  3. 3.Telecommunications CollegeTongji UniversityShanghaiChina
  4. 4.Department of Signals, Systems and RadiocommunicationsTechnical University of MadridMadridSpain

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