A line segment detector for SAR images with controlled false alarm rate

Chenguang Liu, Rémy Abergel, Yann Gousseau, Florence Tupin

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

Abstract

In this paper we propose to adapt LSD [1] (a state-of-the-art line segment detector for optical images) to SAR images. The first modification is replacing the gradient computation with an exponentially weighted ratio-based method which has a constant false alarm rate for SAR images. Next, we observe that the strong noise removal necessary for processing SAR images strongly impairs the independent hypothesis of the a contrario model used by LSD. A first order Markov chain is used to take the spatial dependencies into consideration. Experiments show that the proposed method has good performances and the number of false detections is well controlled.

Original languageEnglish
Title of host publication2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8464-8467
Number of pages4
ISBN (Electronic)9781538671504
DOIs
Publication statusPublished - 31 Oct 2018
Externally publishedYes
Event38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain
Duration: 22 Jul 201827 Jul 2018

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2018-July

Conference

Conference38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Country/TerritorySpain
CityValencia
Period22/07/1827/07/18

Keywords

  • A contrario model
  • First order markov chain
  • LSD
  • Ratio-based

Fingerprint

Dive into the research topics of 'A line segment detector for SAR images with controlled false alarm rate'. Together they form a unique fingerprint.

Cite this