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Automated urban area building extraction from high resolution stereo imagery

机译:从高分辨率立体图像中自动提取市区建筑物

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摘要

This paper describes a new automated building extraction algorithm developed for high resolution stereo imagery. The problems of urban area imagery for stereo matching were investigated. Buildings were found to create isolated regions and many blunders. To overcome the problem of isolated regions, a pyramidal matching algorithm with automatic seed points using a tile-based control strategy was developed. To remove possible blunders and extract buildings from other background objects, a series of 'smart' operations using linear elements from buildings was applied. A quantitative analysis of the accuracy of the algorithm was assessed in comparison with a previous algorithm and shown to have an RMS error of 3.65m in elevation compared to 13.46m.
机译:本文介绍了一种为高分辨率立体图像开发的新的自动建筑物提取算法。研究了用于立体匹配的市区图像问题。人们发现建筑物会产生孤立的区域和许多错误。为了克服孤立区域的问题,开发了一种使用基于图块的控制策略的具有自动种子点的金字塔匹配算法。为了消除可能的错误并从其他背景对象中提取建筑物,应用了一系列使用建筑物中线性元素的“智能”操作。与以前的算法相比,对算法准确性的定量分析进行了评估,结果显示高程RMS误差为3.65m,而13.46m。

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