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Proceedings Paper

Morphological edge detection for oceanographic images
Author(s): Shantha Krishnamurthy; S. Sitharama Iyengar; Ronald J. Holyer; Matthew Lybanon
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Paper Abstract

Mesoscale oceanographic features are important aspects of ocean circulation. The high volume of satellite-derived oceanographic data coupled with the high level of human skill associated with the detection of oceanographic features in the data has necessitated automating the interpretation process. Morphological edge detectors produce better results than the conventional template- and differentiation-based edge detectors. A grayscale morphological edge-detection algorithms is developed for automatic delineation of mesoscale structure in digital satellite IR images of the ocean. We compare performances of three morphological edge detectors in sea surface temperature fields. We provide experimental results on images from the North Atlantic under various image settings.

Paper Details

Date Published: 25 February 1994
PDF: 12 pages
Proc. SPIE 2103, 22nd AIPR Workshop: Interdisciplinary Computer Vision: Applications and Changing Needs, (25 February 1994); doi: 10.1117/12.169465
Show Author Affiliations
Shantha Krishnamurthy, Louisiana State Univ. (United States)
S. Sitharama Iyengar, Louisiana State Univ. (United States)
Ronald J. Holyer, Naval Research Lab. (United States)
Matthew Lybanon, Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 2103:
22nd AIPR Workshop: Interdisciplinary Computer Vision: Applications and Changing Needs
J. Michael Selander, Editor(s)

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