Skip to main content

Towards an automated ocean feature detection, extraction and classification scheme for SAR imagery

Buy Article:

$55.00 plus tax (Refund Policy)

Spaceborne synthetic aperture radar (SAR) observation is an important tool for monitoring and studying changes in various geophysical elements in and above world oceans. Because of SAR's ideal imaging capability and high resolution, the collection of SAR data will likely extend well into the 21st century. As the data become increasingly abundant and computers faster and more affordable, it naturally leads to an increasing need for an automated procedure to replace the labour-intensive manual screening process. In this paper, an integrated scheme for detection, extraction and classification of linear ocean features in SAR imagery is attempted for the purpose of automated screening. The methodology consists of feature detection based on greyscale histogram screening, feature extraction based on two-dimensional wavelet analysis and feature classification based on texture analysis. Using these algorithms on SAR data, several case studies of linear ocean features, including fronts, ice edges and a polar low, are presented herein. Though not fully automated at this stage, the integration of these algorithms seems to lay a promising foundation for the future development of a more automated ocean feature detection, extraction and classification scheme.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: NASA Goddard Space Flight Center, Oceans and Ice Branch, Greenbelt, MD 20771, USA; e-mail: sunny, [email protected]

Publication date: 2003-03-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more