首页> 外文会议>Conference on Automated Geo-Spatial Image and Data Exploitation 24 April 2000 Orlando, USA >Automated spatiotemporal change detection in digital aerial imagery
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Automated spatiotemporal change detection in digital aerial imagery

机译:数字航空影像中的时空变化自动检测

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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化是双重性的挑战。它包括自动更改检测以及建模/表示更改的基本问题。在本文中,我们提出了一种新颖的自动变化检测方法,该方法比常规方法可以更有效地处理变化。更具体地说,我们专注于检测时空GIS环境中建筑物边界的变化。我们开发了一种新颖的方法,作为基于最小二乘的匹配的扩展。将对象的先前空间状态与其在数字图像中的当前表示进行比较,并自动确定轮廓处是否发生了变化。较旧的对象信息用于生成模板,以与较新图像中相同对象的重新呈现进行比较。通过对模板边缘几何形状的分析来提取语义信息,并通过准确性估计来增强我们的方法。这种模板匹配方法使我们可以将具有变化检测功能的数码手指图像提取到单个操作对象中。通过将完整的轮廓分解为较小的元素,并沿这些位置应用模板匹配,我们甚至可以精确地检测出建筑轮廓中的微小变化。在本文中,我们概述了我们的方法,理论模型,某些实施问题,例如模板选择和权重系数分配以及实验结果。

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