Remotely sensed image processing with multi-stage inferences

被引：0

作者：

Yamamoto, H ^{[1
]}

Homma, K ^{[1
]}

Isobe, T ^{[1
]}

Naka, M ^{[1
]}

Matsumura, S ^{[1
]}

Tameishi, H ^{[1
]}

机构：

[1] Natl Aerosp Lab, Chofu, Tokyo 1828522, Japan

来源：

IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING V | 1999年 / 3871卷

关键词：

knowledge-based system; satellite image; mullet-inference;

D O I：

10.1117/12.373237

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：337 / 342

页数：6