Paper
14 December 1999 Remotely sensed image processing with multistage inferences
Hiromichi Yamamoto, Kohzo Homma, Toshio Isobe, Masao Naka, Satsuki Matsumura, Hideo Tameishi
Author Affiliations +
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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiromichi Yamamoto, Kohzo Homma, Toshio Isobe, Masao Naka, Satsuki Matsumura, and Hideo Tameishi "Remotely sensed image processing with multistage inferences", Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); https://doi.org/10.1117/12.373237
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KEYWORDS
Image processing

Image analysis

Satellites

Satellite imaging

Earth observing sensors

Databases

Algorithm development

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