Optimal Selection of Stereo Image Pairs in Planetary Mapping Based on Local and Global Constraints

Mapping of planetary surface using stereo orbital imagery is a basic task of planetary exploration. As the number of orbiter images increases, excessive images will lead to unnecessary time costs and accuracy loss during the photogrammetric mapping process. However, existing studies focus more on the factors that affect the mapping accuracy and often ignores the redundancy and distribution rationality of images in the mapping process. Therefore, optimal data selection from extremely redundant orbiter images has become a challenging and urgent issue for planetary mapping. This paper proposes an effective optimal selection method of off-track stereo pairs, which extends the selection operation from a local to a global perspective, and reduces the redundancy of image pair subset covering the region of interest (ROI) based on multi-constraints such as quality constraints and global distribution constraints. Specifically, the ROI is rasterized and gridded, and the optimal and candidate stereo pairs are selected for each grid based on the quantified quality constraints. By combining global distribution constraints and consistency constraints between adjacent stereo pairs, an optimization model is constructed and the optimal subset of stereo pairs is determined using belief propagation algorithm. Experiments conducted on the selected ROIs of Moon and Mars indicate that our method significantly reduces data redundancy while ensuring the quality and rational distribution of stereo image pairs. Qualitative and quantitative evaluations demonstrate that the stereo pairs obtained using the proposed method perform exceptionally well in terms of intersection angles, redundancy rates, and other factors, showing overall superior performance compared to other methods. Additionally, the stereo pairs obtained by the proposed method were employed for photogrammetric mapping within the ROI, and the results validate the mapping products also exhibit satisfactory accuracy.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3582819
Primary Topic
Satellite Image Processing and Photogrammetry
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimal Selection of Stereo Image Pairs in Planetary Mapping Based on Local and Global Constraints

Huan Xie, Rong Huang, Xiaohua Tong, Zhen Ye et al.
IEEE Transactions on Geoscience and Remote Sensing
Satellite Image Processing and Photogrammetry
article

Optimal Selection of Stereo Image Pairs in Planetary Mapping Based on Local and Global Constraints

Huan Xie, Rong Huang, Xiaohua Tong, Zhen Ye, Changjiang Xiao, Yusheng Xu, Dayong Liu, Miyu Zhou
article en

Abstract

Mapping of planetary surface using stereo orbital imagery is a basic task of planetary exploration. As the number of orbiter images increases, excessive images will lead to unnecessary time costs and accuracy loss during the photogrammetric mapping process. However, existing studies focus more on the factors that affect the mapping accuracy and often ignores the redundancy and distribution rationality of images in the mapping process. Therefore, optimal data selection from extremely redundant orbiter images has become a challenging and urgent issue for planetary mapping. This paper proposes an effective optimal selection method of off-track stereo pairs, which extends the selection operation from a local to a global perspective, and reduces the redundancy of image pair subset covering the region of interest (ROI) based on multi-constraints such as quality constraints and global distribution constraints. Specifically, the ROI is rasterized and gridded, and the optimal and candidate stereo pairs are selected for each grid based on the quantified quality constraints. By combining global distribution constraints and consistency constraints between adjacent stereo pairs, an optimization model is constructed and the optimal subset of stereo pairs is determined using belief propagation algorithm. Experiments conducted on the selected ROIs of Moon and Mars indicate that our method significantly reduces data redundancy while ensuring the quality and rational distribution of stereo image pairs. Qualitative and quantitative evaluations demonstrate that the stereo pairs obtained using the proposed method perform exceptionally well in terms of intersection angles, redundancy rates, and other factors, showing overall superior performance compared to other methods. Additionally, the stereo pairs obtained by the proposed method were employed for photogrammetric mapping within the ROI, and the results validate the mapping products also exhibit satisfactory accuracy.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Tongji University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Climate action
Openalex Percentile: Top 82%
Satellite Image Processing and Photogrammetry
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