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Proceedings Paper

Remotely sensed image processing with multistage inferences
Author(s): Hiromichi Yamamoto; Kohzo Homma; Toshio Isobe; Masao Naka; Satsuki Matsumura; Hideo Tameishi
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Paper Abstract

A system for analyzing remotely-sensed satellite images using knowledge bases driven by multi-stage inference engines has been developed. Sea-surface temperature analysis is thought to have great potential for effectively identifying the positions and shapes of oceanic conditions such as ocean fronts, eddies, currents, and so on. Knowledge and experience accumulated through conventional oceanic observation by ships and other methods are indispensable when extracting such oceanic conditions from remotely-sensed data, and the extraction process requires the efforts of human experts. This paper discusses some useful strategies for dealing with the problems of automatic extraction of oceanic conditions, including a mechanism for selecting individual algorithms and automatically constructing a sequence of image processing commands, a scheme for verifying consistency between knowledge rules, and a scheme for the intensive accumulation of knowledge information. In addition, this paper presents some experimental applications to remotely-sensed ocean image data which have been performed highly efficiently. The resulting extracted ocean fronts and currents have been successfully verified using oceanographic surveys.

Paper Details

Date Published: 14 December 1999
PDF: 6 pages
Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); doi: 10.1117/12.373237
Show Author Affiliations
Hiromichi Yamamoto, National Aerospace Lab. (Japan)
Kohzo Homma, National Aerospace Lab. (Japan)
Toshio Isobe, National Aerospace Lab. (Japan)
Masao Naka, Remote Sensing Technology Ctr. (Japan)
Satsuki Matsumura, National Research Institute of Far Seas Fisheries (Thailand)
Hideo Tameishi, Japan Fisheries Information Service Ctr. (Japan)


Published in SPIE Proceedings Vol. 3871:
Image and Signal Processing for Remote Sensing V
Sebastiano Bruno Serpico, Editor(s)

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