沙洪俊, 袁修孝. 双目影像密集匹配方法的回顾与展望[J]. 武汉大学学报 ( 信息科学版), 2023, 48(11): 1813-1833. DOI: 10.13203/j.whugis20230037
引用本文: 沙洪俊, 袁修孝. 双目影像密集匹配方法的回顾与展望[J]. 武汉大学学报 ( 信息科学版), 2023, 48(11): 1813-1833. DOI: 10.13203/j.whugis20230037
SHA Hongjun, YUAN Xiuxiao. State-of-the-Art Binocular Image Dense Matching Method[J]. Geomatics and Information Science of Wuhan University, 2023, 48(11): 1813-1833. DOI: 10.13203/j.whugis20230037
Citation: SHA Hongjun, YUAN Xiuxiao. State-of-the-Art Binocular Image Dense Matching Method[J]. Geomatics and Information Science of Wuhan University, 2023, 48(11): 1813-1833. DOI: 10.13203/j.whugis20230037

双目影像密集匹配方法的回顾与展望

State-of-the-Art Binocular Image Dense Matching Method

  • 摘要: 以摄影测量为应用背景,综述了双目影像密集匹配方法。首先借助图表对局部密集匹配与全局密集匹配两类方法进行了简明的比较,指出各类方法的优缺点以及面临的主要挑战;然后分析了密集匹配中难以处理的建筑物遮挡问题,将航摄影像中普遍存在的建筑物遮挡现象分为5种类型,阐述了现有遮挡检测与填充算法的针对性,为解决密集匹配中的空洞问题提供技术思路;最后展望了双目影像密集匹配的发展趋势。以期帮助读者全面了解传统双目影像密集匹配技术,对基于深度学习的密集匹配研究有所裨益。

     

    Abstract: Based on the application in the field of photogrammetry, this paper retrospects the binocular image dense matching method. First, the two categories of local dense image matching and global dense image matching methods are concisely compared, and the advantages, disadvantages, and main challenges of each method are pointed out. Then, the building occlusion problem that is difficult to deal with in dense matching is analyzed. The common building occlusion phenomenon in aerial photography is divided into five types, and the pertinence of the existing occlusion detection and filling algorithms is expounded, which provides technical ideas for solving the bottleneck problem in dense image matching. Finally, the development trend of dense image matching of binocular images is prospected. This paper can help readers fully understand the traditional binocular image dense matching technology, and it will be beneficial to the research of dense image matching based on deep learning.

     

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