ABSTRACT The aim of site planning based on multiple viewshed analysis is to select the minimum number of viewpoints that maximize visual coverage over a given terrain. However, increasingly high-resolution terrain data means that the number of terrain points will increase rapidly, which will lead to rapid increases in computational requirements for multiple viewshed site planning. In this article, we propose a fast Candidate Viewpoints Filtering (CVF) algorithm for multiple viewshed site planning to lay a foundation for viewpoint optimization selection. Firstly, terrain feature points are selected as candidate viewpoints. Then, these candidate viewpoints are clustered and those belonging to each cluster are sorted according to the index of viewshed contribution (IVC). Finally, the candidate viewpoints with relatively low viewshed contribution rate are removed gradually using the CVF algorithm, through which, the viewpoints with high viewshed contribution are preserved and the number of viewpoints to be preserved can be controlled by the number of clusters. To evaluate the effectiveness of our CVF algorithm, we compare it with the Region Partitioning for Filtering (RPF) and Simulated Annealing (SA) algorithms. Experimental results show that our CVF algorithm is a substantial improvement in both computational efficiency and total viewshed coverage rate.

中文翻译：

---

一种用于多视域站点规划的快速候选视点过滤算法

摘要 基于多视域分析的站点规划的目的是选择最小数量的视点，以最大化给定地形上的视觉覆盖。然而，越来越高分辨率的地形数据意味着地形点的数量将迅速增加，这将导致多视域站点规划的计算需求快速增加。在本文中，我们提出了一种用于多视域站点规划的快速候选视点过滤（CVF）算法，为视点优化选择奠定基础。首先，选择地形特征点作为候选视点。然后，对这些候选视点进行聚类，并根据视域贡献指数（IVC）对属于每个聚类的视点进行排序。最后，采用CVF算法逐步去除视域贡献率相对较低的候选视点，保留视域贡献率较高的视点，并通过簇数控制要保留的视域数量。为了评估我们的 CVF 算法的有效性，我们将其与区域划分过滤 (RPF) 和模拟退火 (SA) 算法进行了比较。实验结果表明，我们的 CVF 算法在计算效率和总视域覆盖率方面都有实质性的提高。我们将其与区域划分过滤 (RPF) 和模拟退火 (SA) 算法进行比较。实验结果表明，我们的 CVF 算法在计算效率和总视域覆盖率方面都有实质性的提高。我们将其与区域划分过滤 (RPF) 和模拟退火 (SA) 算法进行比较。实验结果表明，我们的 CVF 算法在计算效率和总视域覆盖率方面都有实质性的提高。