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首页> 外文期刊>International journal of knowledge and systems science >A Layered Architecture for a Fuzzy Semantic Approach for Satellite Image Analysis
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A Layered Architecture for a Fuzzy Semantic Approach for Satellite Image Analysis

机译：用于卫星图像分析的模糊语义方法的分层体系结构

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摘要

The extended use of high and very high spatial resolution imagery inherently demands the adoption of classification methods capable of capturing the underlying semantic. Object-oriented classification methods are currently considered as the most appropriate alternative, due to the incorporation of contextual information and domain knowledge into the analysis. Integrating knowledge initially requires a detailed process of acquisition and later the achievement of a formal representation. Ontologies constitute a very suitable approach to address both knowledge formalization and exploitation. A novel semi-automatic fuzzy semantic approach focused on the extraction and classification of urban objects is hereby introduced. The use of a four-layered architecture allows the separation of concerns among knowledge, rules, experience and meta-knowledge. Knowledge represents the fundamental layer with which the other layers interact. Rules are meant to derive conclusions and make assertions based on knowledge. The experience layer supports the classification process in case of failure when attempting to identify an object, by applying specific expert rules to infer unusual membership. Finally, the meta-knowledge layer contains knowledge about the use of the other layers.
机译：高和非常高的空间分辨率图像的广泛使用本质上要求采用能够捕获基本语义的分类方法。由于将上下文信息和领域知识合并到分析中，因此面向对象的分类方法目前被认为是最合适的选择。整合知识最初需要一个详细的获取过程，后来需要一个正式的表示形式。本体是解决知识形式化和利用问题的非常合适的方法。本文介绍了一种新颖的半自动模糊语义方法，重点研究了城市物体的提取和分类。使用四层体系结构可以将知识，规则，经验和元知识之间的关注点分离。知识代表与其他层交互的基础层。规则旨在得出结论并根据知识做出断言。经验层通过应用特定的专家规则来推断异常成员身份，从而在尝试识别对象失败时支持分类过程。最后，元知识层包含有关其他层使用的知识。

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