An efficient and precise multi-candidate viewpoint filtering algorithm for terrain viewshed selection

Abstract

The goal of terrain viewshed point selection is to identify multiple viewpoints within a specific area that offer optimal visibility. However, as the resolution of terrain data becomes finer, the number of data points to be processed grows significantly, leading to a sharp rise in computational demands for viewshed point selection. This paper introduces the Efficient Precise Viewshed Point Selection (EPVPS) algorithm, which provides an important reference for multi-viewpoint planning. First, the Empty Circles based K-means (ECKM) algorithm is utilized to determine the initial centers for candidate viewpoint clustering. Second, a new viewpoint evaluation metric, Weighted Coverage Overlap Metric (WCOM), is proposed. This metric divides the viewshed of candidate points into coverage contribution points and overlap contribution points, computes WCOM based on this division, and stores the values in a min-heap. Finally, viewpoints are added and deleted from clusters by adjusting the sets of coverage contribution points and overlap contribution points. The EPVPS algorithm is compared with the Candidate Viewpoints Filtering (CVF) algorithm and the Simulated Annealing (SA) algorithm. Experimental results demonstrate that the EPVPS algorithm outperforms the others in computational efficiency, coverage rate, and overlap rate.