Paper
28 January 2025 A fast parallel algorithm for image elevation datum conversion based on multicore technology
Xinhao Fan, Hengjing Zhang
Author Affiliations +
Proceedings Volume 13506, Sixth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2024); 135061Y (2025) https://doi.org/10.1117/12.3057593
Event: Sixth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2024), 2024, Qingdao, China
Abstract
Aiming at the prominent problem of low efficiency in the process of elevation datum transformation of DEM or DSM images, a fast calculation method based on MPI ( Message Passing Interface ) parallel technology is proposed. The purpose is to use multi-core technology to effectively accelerate the working speed and comprehensively improve the efficiency and quality of elevation datum transformation. The experiment uses two sets of DEM images with different image resolutions (DEM images are used in this paper due to the same processing method of DSM images and DEM images), and conducts batch image elevation datum conversion experiments on the Ubutun 20.4.3LTS operating system. The experiment uses the MPI parallel algorithm to make full use of the performance advantages of multi-core computers to achieve the purpose of processing multiple images at the same time. The results show that the use of MPI parallel technology can greatly improve the efficiency of image elevation datum conversion. The efficiency of using this method to calculate two sets of images is increased by 10.9 and 10.859 times, respectively. MPI parallel technology can give full play to the advantages of multi-core computers, and the parallel effect is best when the number of processes is about the total number of tasks.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xinhao Fan and Hengjing Zhang "A fast parallel algorithm for image elevation datum conversion based on multicore technology", Proc. SPIE 13506, Sixth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2024), 135061Y (28 January 2025); https://doi.org/10.1117/12.3057593
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