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A VECTOR MACHINE BASED APPROACH TOWARDS OBJECT ORIENTED CLASSIFICATION OF REMOTELY SENSED IMAGERY

机译:基于矢量机的面向对象的遥感图像分类方法

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摘要

Remote sensing techniques are widely used for land cover classification and related analyses; however the availability of high resolution images have limited the accuracy of pixel based approaches. In this paper, we have analyzed the feasibility of incorporating contextual information to a support machine and have evaluated its performances with reference to the traditional approaches. We have adopted certain automatic approaches based on advanced techniques such as Cellular Automata and Genetic Algorithm for improving effective overlap between classes. Proposed methodology has been evaluated in comparison with the conventional approaches with reference to the study area using relevant statistical parameters. Accuracy improvement of the proposed approach may be attributed to the effectiveness in combining spatial and spectral information.
机译:遥感技术被广泛用于土地覆被分类和相关分析;然而,高分辨率图像的可用性限制了基于像素的方法的准确性。在本文中,我们分析了将上下文信息合并到支持机器的可行性,并参考传统方法评估了它的性能。我们采用了基于自动技术(例如细胞自动机和遗传算法)的某些自动方法来改善类之间的有效重叠。使用相关的统计参数,参照研究区域,与常规方法进行了比较,对所提出的方法进行了评估。所提出的方法的准确性的提高可以归因于组合空间和频谱信息的有效性。

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