数字高程图地质配准的信息论方法

Miguel Aguilera, A. Hamza
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引用次数: 5

摘要

数字高程图的地理配准是融合传感器数据的关键步骤。本文提出了一种利用莫尔斯奇点的熵配准方法。我们提出的方法背后的核心思想是将高程图编码为一组莫尔斯奇点。在此基础上,利用信息理论对目标和参考图的摩尔斯特征进行最大不相似度度量,使高程数据对齐。我们还表明,最大化这种散度度量导致最小化两个高程数据图的联合最小生成树的总长度。实验结果表明,该方法具有较好的鲁棒性和配准精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Information-Theoretic Approach to Georegistration of Digital Elevation Maps
Georegistration of digital elevation maps is a vital step in fusing sensor data. In this paper, we present an entropic registration method using Morse singularities. The core idea behind our proposed approach is to encode an elevation map into a set of Morse singular points. Then an information-theoretic dissimilarity measure between the Morse features of the target and the reference maps is maximized to bring the elevation data into alignment. We also show that maximizing this divergence measure leads to minimizing the total length of the joint minimal spanning tree of both elevation data maps. Illustrating experimental results are presented to show the robustness and the georegistration accuracy of the proposed approach.
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