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A cognitive based approach for building detection from high resolution satellite images

机译:基于认知的从高分辨率卫星图像进行建筑物检测的方法

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High resolution satellite images are new sources of data for geo-spatial information. In order to automate the process of extraction of information from satellite images emulating human experts, an understanding of the human cognitive processes involved in information extraction from images are required. The objective of this research work is to emulate the human cognitive capabilities by integrating cognitive task analysis for extraction of data from satellite images. Initially, preliminary knowledge about the sequence of cognitive processes which human being utilizes during the interpretation and classification of images was collected. Here, rule based approach for the representation of the knowledge which is obtained from the visual interpretation of image by the human beings. Defined rules are used to determine the buildings in the satellite images using the mixture tuned matched filtering algorithm (MTMF). Further, during knowledge elicitation the domain knowledge is grouped together using support vector classifier. The method is tested using four different sets of high resolution satellite images. The overall average of precision and recall are computed as 99.08% and 75.85%, respectively.
机译:高分辨率卫星图像是地理空间信息的新数据源。为了使从模拟人类专家的卫星图像中提取信息的过程自动化,需要了解与从图像中提取信息有关的人类认知过程。这项研究工作的目的是通过整合认知任务分析以从卫星图像中提取数据来模拟人类的认知能力。最初,收集了有关人类在图像的解释和分类过程中利用的认知过程序列的初步知识。这里,是一种基于规则的方法,用于表示知识,该知识是从人类对图像的视觉解释中获得的。定义的规则用于使用混合调谐匹配滤波算法(MTMF)确定卫星图像中的建筑物。此外,在知识获取期间,使用支持向量分类器将领域知识分组在一起。使用四组不同的高分辨率卫星图像测试了该方法。精确度和召回率的总体平均值分别为99.08%和75.85%。

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