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Automated spatiotemporal change detection in digital aerial imagery

机译:数字空中图像中自动的时空变化检测

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Handling change within integrated geospatial environments is a challenge of dual nature. It comprises automatic change detection, and the fundamental issue of modeling/representing change. In this paper we present a novel approach for automated change detection which allows us to handle change more effiicently than commonly available approache4s. More specifically, we focus on the detection of building boundary changes within a spatiotemporal GIS environment. We have developed a novel approach, as an extension of least-squares based matching. Previous spatial states of an object are compared to its current representation in a digital image, and decisions are automatically made as to whether or not change at the outline has occurred. Older object informaiton is used to produce templates for comparison with the represnetation of the same object in a newer image. Semantic informaiton extracted through an analysis of template edge geometry, and estimates of accuracy are used to enhance our method. This template matching approach allows us to integrate in a single operation object extraction from digitla imagery with change detection. By decomposing a complete outline into smaller elements and applying template matching along these locations we are able to detect precisely even small changes in building outlines. In this paper we present an overview of our apporach, theoretical models, certain, implementation issues like template selection and weight coeffiicent assignment, and experimental results.
机译:在集成的地理空间环境中处理变更是双重性质的挑战。它包括自动变更检测,以及建模/代表变更的基本问题。在本文中,我们提出了一种用于自动变化检测的新方法,其允许我们比常见的方法4S更有效力地处理变化。更具体地说,我们专注于在时空GIS环境内的建筑边界变化的检测。我们开发了一种新颖的方法,作为基于最小二乘匹配的延伸。将对象的先前的空间状态与其数字图像中的当前表示进行比较,并且自动做出决定是否发生了轮廓处的改变。旧对象信息用于生成模板,以便与较新图像中的同一对象的HapdingNation进行比较。通过对模板边缘几何的分析提取的语义信息,并使用精度估计来增强我们的方法。此模板匹配方法允许我们在从Digitla Imagery中提取的单个操作对象提取,改变检测。通过将完整的大纲分解成较小的元素并沿着这些位置应用模板,我们能够在建筑轮廓中恰好检测甚至的小变化。在本文中,我们概述了我们的Apporach,理论模型,某些实施问题,如模板选择和体重系数分配以及实验结果。

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