In order to raise the intelligent level and improve cooperative ability of grid. This paper proposes an agent oriented
middleware, which is applied to the traditional OGSA architecture to compose a new architecture named CIG
(Cooperative Intelligent Grid) and expounds the types of cooperative processing of remote sensing, the architecture of
CIG and how to implement the cooperation in the CIG environment.
KEYWORDS: Image processing, Remote sensing, Computing systems, Web services, Data processing, Sensing systems, Databases, Image compression, Internet, Local area networks
In this article, a remote sensing image processing system is established to carry out the significant scientific problem that
processing and distributing the mass earth-observed data quantitatively and intelligently with high efficiency under the
Condor Environment. This system includes the submitting of the long-distantly task, the Grid middleware in the mass image processing and the quick distribution of the remote-sensing images, etc. A conclusion can be gained from the application of this system based on Grid environment. It proves to be an effective way to solve the present problem of fast processing, quick distribution and sharing of the mass remote-sensing images.
When using ontological theory to set up remote sensing image knowledge system, the majority of scholars by now
regard ontology as logical theory for defining the object, attribution relation, affair and process of remote sending
knowledge system. But understanding and describing the real world makes that logical theory be unable to unify
concepts with the same practical meaning from different concept models, so bring grid service system drawbacks in
knowledge delivering and sharing. To solve that issue requires further improvement of the defining method and model
for concepts in ontology. This paper presents a neural network remote sensing image ontological concept extraction
model based on image understanding and describing, utilize the theory of bionic optimization, and adopts the
combination of artificial neural network with the rule-based knowledge Recognition System. Realize the knowledge
delivering and sharing among different information systems or make the knowledge delivering and sharing between
client and system possible and effective.
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