Segmentation of multispectral images and prediction of ChI-a concentration for effective ocean colour remote sensing

Jinchang Ren, Xuexing Zeng, David McKee

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

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Abstract

With the development of new sensors and data processing techniques, ocean colour remote sensing has undergone rapid development in more accurately measurement of coastal shelf classification and concentration of chlorophyll. In this paper, multispectral images are employed to achieve these targets, using techniques including region-growing based segmentation for pixel classification and support vector regression for ChI-a prediction. Interesting results are reported to show the great potential in using state-of-the-art data analysis techniques for effective ocean colour remote sensing.
Original languageEnglish
Title of host publication2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages2303-2306
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

  • ocean colour remote sensing
  • coastal classification
  • chlorophyll concentration measurement
  • image segmentation
  • multispectral/hyperspectral imaging

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