Improved algorithm for occlusion detection in large tilt aerial images based on elevation constraints

Yu Liu; Dejun Li; Zhaohong Xu; Shangwen Sun

doi:10.1117/12.3029642

21 June 2024 Improved algorithm for occlusion detection in large tilt aerial images based on elevation constraints

Yu Liu, Dejun Li, Zhaohong Xu, Shangwen Sun

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131672E (2024) https://doi.org/10.1117/12.3029642
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

To improve the accuracy and efficiency of detecting occluded areas in large tilt images, this paper improves the Occlusion Detection Algorithm Based on Elevation Constraints on the basis of Angle Based Occlusion Detection Algorithm, and proposes an Occlusion Detection Algorithm Based on Elevation and Angle Constraints. This algorithm uses the spiral scanning method to judge the visibility of ground points layer by layer from the underground point, and fully utilizes the elevation, elevation angle with projection center, and visibility information of the inner layer point to judge the current point, greatly reducing the number of points that need to be judged. Compared with existing classical algorithms, it has the advantages of high accuracy and fast visibility analysis speed.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yu Liu, Dejun Li, Zhaohong Xu, and Shangwen Sun "Improved algorithm for occlusion detection in large tilt aerial images based on elevation constraints", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131672E (21 June 2024); https://doi.org/10.1117/12.3029642

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