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Ship detection in a large scene SAR image using image uniformity description factor

  • Harbin Institute of Technology

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

Abstract

Effective features extraction and high speed processing algorithms are key points for large scene SAR image processing, such as ship detection in the ocean. Feature based ship detection methods can use more information about targets and make results robust in different backgrounds. Although texture is an effective and strong feature in SAR images, its large computation time limits its practice in SAR applications. In this paper, a new texture feature named Image Uniformity Description Factor (IUDF) is proposed to extract uniformity information of SAR images and is used to design a texture based large scene SAR image ship detection algorithm in which accuracy and processing time are taken into consideration as two indexes to test the usefulness of IUDF in practical application. Experiment results show that the algorithm proposed using IUDF can be applied for ship detection in SAR images with a high accuracy and processing speed.

Original languageEnglish
Title of host publicationProceedings of 2017 SAR in Big Data Era
Subtitle of host publicationModels, Methods and Applications, BIGSARDATA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538645192
DOIs
StatePublished - 29 Nov 2017
Event2017 SAR in Big Data Era: Models, Methods and Applications, BIGSARDATA 2017 - Beijing, China
Duration: 13 Nov 201714 Nov 2017

Publication series

NameProceedings of 2017 SAR in Big Data Era: Models, Methods and Applications, BIGSARDATA 2017
Volume2017-January

Conference

Conference2017 SAR in Big Data Era: Models, Methods and Applications, BIGSARDATA 2017
Country/TerritoryChina
CityBeijing
Period13/11/1714/11/17

Keywords

  • Image uniformity
  • Large scene sar image
  • Ship detection
  • Texture

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