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Context-sensitive Filtering of Terrain Data based on Multi Scale Analysis

机译:基于多尺度分析的地形数据的上下文敏感滤波

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This paper addresses triangle count reduction for regular terrain triangulations. Supported by additional information available from cadastre data, non-linear low pass filtering based on wavelet coefficients is applied. The aim is to generate a simplified view of a city model's terrain so that still landmarks can be easily recognized. Height data, that are not critical for visual impressions, are compressed with lower resolution than height data belonging to landmarks. Results are presented for the German city of Krefeld.
机译:本文解决了常规地形三角形的三角形计数。 由Cadastre数据提供的附加信息支持,应用了基于小波系数的非线性低通滤波。 目的是生成一个简化的城市模型的地形观点,以便仍然可以容易地识别仍然具有地标。 对视觉印象不关键的高度数据被压缩,而不是属于地标的高度数据。 结果是德国克雷福德市的结果。

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