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Detection and analysis of change in remotely sensed imagery with application to wide area surveillance

机译:遥感影像变化的检测与分析及其在广域监视中的应用

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摘要

A new approach to wide area surveillance is described that is based on the detection and analysis of changes across two or more images over time. Methods for modeling and detecting general patterns of change associated with construction and other kinds of activities that can be observed in remotely sensed imagery are presented. They include a new nonlinear prediction technique for measuring changes between images and temporal segmentation and filtering techniques for analyzing patterns of change over time. These methods are applied to the problem of detecting facility construction using Landsat Thematic Mapper imagery. Full scene results show the methods to be capable of detecting specific patterns of change with very few false alarms. Under all conditions explored, as the number of images used increases, the number of false alarms decreases dramatically without affecting the detection performance. It is argued that the processing gain that results in using more than two images justifies the increased computational complexity and storage requirements of our approach over single image object detection and conventional change detection techniques.
机译:描述了一种新的广域监视方法,该方法基于对两个或多个图像随时间变化的检测和分析。提出了建模和检测与建筑和其他种类的活动相关的一般变化模式的方法,这些变化可以在遥感影像中观察到。它们包括用于测量图像之间的变化和时间分段的新的非线性预测技术,以及用于分析随时间变化的模式的滤波技术。这些方法适用于使用Landsat Thematic Mapper影像检测设施建设的问题。全场景结果表明,该方法能够在极少的误报情况下检测特定的变化模式。在探索的所有条件下,随着使用的图像数量的增加,错误警报的数量将大大减少而不会影响检测性能。有人认为,导致使用多于两个图像的处理增益证明了我们的方法相对于单个图像对象检测和常规更改检测技术所增加的计算复杂性和存储要求。

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