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A new coastline extraction in remote sensing images

  • Xing Kun*
  • , Fu Yili
  • , Zhou Feng
  • *Corresponding author for this work
  • China Aerospace Science and Technology Corporation

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

Abstract

While executing tasks such as ocean pollution monitoring, maritime rescue, geographic mapping, and automatic navigation utilizing remote sensing images, the coastline feature should be determined. Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image. Active contour model, also called snakes, have proven useful for interactive specification of image contours, so it is used as an effective coastlines extraction technique. Firstly, coastlines are detected by water segmentation and boundary tracking, which are considered initial contours to be optimized through active contour model. As better energy functions are developed, the power assist of snakes becomes effective. New internal energy has been done to reduce problems caused by convergence to local minima, and new external energy can greatly enlarge the capture region around features of interest. After normalization processing, energies are iterated using greedy algorithm to accelerate convergence rate. The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.

Original languageEnglish
Title of host publicationImage and Signal Processing for Remote Sensing XVIII
DOIs
StatePublished - 2012
EventImage and Signal Processing for Remote Sensing XVIII - Edinburgh, United Kingdom
Duration: 24 Sep 201226 Sep 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8537
ISSN (Print)0277-786X

Conference

ConferenceImage and Signal Processing for Remote Sensing XVIII
Country/TerritoryUnited Kingdom
CityEdinburgh
Period24/09/1226/09/12

Keywords

  • Active contour model
  • Coastline extraction
  • External energy
  • Greedy algorithm
  • Image contours
  • Internal energy
  • Remote sensing images
  • Water segmentation

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