Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach

Jinchang Ren, Byongjun Hwang, Paul Murray, Soumitra Sakhalkar, Samuel McCormack

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

4 Citations (Scopus)
125 Downloads (Pure)

Abstract

Accurate sea-ice segmentation from satellite synthetic aperture radar (SAR) images plays an important role for understanding the interactions between sea-ice, ocean and atmosphere in the Arctic. Processing sea-ice SAR images are challenging due to poor spatial resolution and severe speckle noise. In this paper, we present a multi-stage method for the sea-ice SAR image segmentation, which includes edge-preserved filtering for pre-processing, k-means clustering for segmentation and conditional morphology filtering for post-processing. As such, the effect of noise has been suppressed and the under-segmented regions are successfully corrected.
Original languageEnglish
Title of host publication2015 IEEE International Geoscience and Remote Sensing Symposium
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages1040-1043
Number of pages4
ISBN (Print)9781479979295
DOIs
Publication statusAccepted/In press - 3 Apr 2015
EventIEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015) - Convention Center, Milan, Italy
Duration: 26 Jul 201531 Jul 2015

Conference

ConferenceIEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015)
Abbreviated titleIGARSS 2015
CountryItaly
CityMilan
Period26/07/1531/07/15

Keywords

  • sea ice image segmentation
  • satellite synthetic aperture radar
  • edge-preserved filtering
  • k-means clustering
  • conditional morphology filtering
  • remote sensing

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