A Generalized Voronoi Diagram-Based Segment-Point Cyclic Line Segment Matching Method for Stereo Satellite Images

Abstract

Matched line segments are crucial geometric elements for reconstructing the desired 3D structure in stereo satellite imagery, owing to their advantages in spatial representation, complex shape description, and geometric computation. However, existing line segment matching (LSM) methods face significant challenges in effectively addressing co-linear interference and the misdirection of parallel line segments. To address these issues, this study proposes a “continuous–discrete–continuous” cyclic LSM method, based on the Voronoi diagram, for stereo satellite images. Initially, to compute the discrete line-point matching rate, line segments are discretized using the Bresenham algorithm, and the pyramid histogram of visual words (PHOW) feature is assigned to the line segment points which are detected using the line segment detector (LSD). Next, to obtain continuous matched line segments, the method combines the line segment crossing angle rate with the line-point matching rate, utilizing a soft voting classifier. Finally, local point-line homography models are constructed based on the Voronoi diagram, filtering out misdirected parallel line segments and yielding the final matched line segments. Extensive experiments on the challenging benchmark, WorldView-2 and WorldView-3 satellite image datasets, demonstrate that the proposed method outperforms several state-of-the-art LSM methods. Specifically, the proposed method achieves F1-scores that are 6.22%, 12.60%, and 18.35% higher than those of the best-performing existing LSM method on the three datasets, respectively.