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High precision and fast disparity estimation via parallel phase correlation hierarchical framework

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Abstract

When estimating the disparity of remote sensing images, known phase correlation (PC)-based disparity estimation methods are not fast and robust, such as hierarchical structure PC method and fixed window PC method. To tackle this problem, a parallel PC-based hierarchical framework is proposed, which includes two ideas: first, a weighted PC peak fitting algorithm is introduced for estimating the high precise disparity matrix efficiently and stably; second, a graphics processing unit-based parallel PC algorithm is integrated into the hierarchical framework for fast and robustly estimating high precise disparity map. Additionally, many stages of hierarchical framework, such as padding and reliable evaluation stages, are improved for improving the computational efficiency of disparity estimation system. In a large number of experiments, the results have shown that the efficiency of the proposed algorithm is on average 24 times faster than the compared state-of-the-art methods. Meanwhile, the precision of the proposed algorithm is also superior to or very close to the compared algorithms. The proposed algorithm has been successfully used in a unmanned aerial vehicle three-dimensional retrieval system, and the practice effect has also been verified.

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Acknowledgements

Thank the Editor and Reviewers for spending time and effort handling this paper. Thank Yixuan Li, Haorong Wang and Shuangli Du for helping us proofread manuscript. Additionally, thank Tao Chen and Baojiang Liu for the technique support. This work was supported in part by the National Natural Science Foundation of China under Grants 61801279, 61860206007, 61571313 and u1633126, in part by the Shanxi Province Science Foundation under Grant 201801D221160, and in part by Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi (STIP) under Grant 2019L0471, and in part by Shanxi University of Finance and Economics Research Fund for Young Scholars under Grant QN-2018005.

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  1. College of Information Science, Shanxi University of Finance and Economics, Taiyuan, 030006, China

    Jie Li

  2. College of Computer Science, Sichuan University, Chengdu, 610065, China

    Yiguang Liu

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  1. Jie Li
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Li, J., Liu, Y. High precision and fast disparity estimation via parallel phase correlation hierarchical framework. J Real-Time Image Proc 18, 463–479 (2021). https://doi.org/10.1007/s11554-020-00972-1

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