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Remote Sensing Image Change Detection Based on Swarm Intelligent Algorithm

机译:基于群体智能算法的遥感影像变化检测

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For several decades the remote sensing change detection methods for depicting land cover have gained a great achievements, and the artificial intelligence techniques have being applied to remote sensing data processing and show great potential. Ant colony optimization (ACO) and Particle swarm optimization (PSO) as the two main algorithms of swarm intelligence, and because of the self-organization, cooperation, communication and other intelligent merits, they have great potential in research area. This paper introduces remotely sensed image change detection using the swarm intelligent algorithm. Selecting Landsat-5 TM image located in Beijing area as experimental data, this paper use the algorithm for constructing the change rules, then use these rules to process the example data, the experiment results show that warm intelligent algorithm has provided a new method for remote sensing image change detection.
机译:几十年来,描绘陆地覆盖的遥感变化检测方法已经获得了巨大的成就,并且人工智能技术已经应用于遥感数据处理并显示出很大的潜力。蚁群优化(ACO)和粒子群优化(PSO)作为群体智能的两个主要算法,而且由于自组织,合作,沟通等智能优点,它们在研究领域有很大的潜力。本文介绍了使用Swarm智能算法的远程感测的图像变化检测。选择Landsat-5 TM图像位于北京地区作为实验数据,本文使用算法来构建变更规则,然后使用这些规则来处理示例数据,实验结果表明,温暖智能算法为遥控器提供了新的方法感应图像改变检测。

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