低空摄影测量立体影像匹配的现状与展望

doi:10.11947/j.AGCS.2019.20190466

摘要/Abstract

摘要： 影像匹配是在两幅或多幅具有重叠度的影像中通过特定的算法提取影像间同名点的过程，是低空摄影测量数据处理中最为关键的步骤，匹配质量与效率直接影响到后续数据处理的成功与否，关系到测绘产品生成质量。本文系统阐述了低空摄影测量影像匹配的研究现状与展望。对影像匹配的分类进行总结和归纳，大体上，影像匹配可划分为两大类，即基于灰度和基于特征的匹配。重点针对基于特征的影像匹配，从点、线、面等特征提取算法及特征描述符和相似性测度与策略等方面进行了详细阐述。此外，列举最新的基于深度学习的影像匹配算法，对低空平台搭载的多样化传感器数据融合可能涉及的影像匹配方法进行了展望。

关键词: 影像匹配, 低空摄影测量, 特征提取, 深度学习

Abstract: Image matching is the process of obtaining corresponding points between two or more overlapping images by a specific algorithm. It is the critical step in the low-altitude photogrammetric data processing. The quality and efficiency of matching directly affect the subsequent data processing and the quality of mapping product generation. Therefore, image matching is one of the hot topics in the field of low-altitude photogrammetry and many relevant algorithms have been proposed. In this paper, the research status and prospect of image matching in low-altitude photogrammetry are described systematically. Firstly, the categories of image matching are summarized and can be generally divided into gray- and feature-based matching. We focus on feature-based image matching, e.g., point, line, and region-based features extraction and the relevant descriptors and similarity measures are described in detail. Besides, the latest image matching algorithms based on deep learning are listed, and the image matching methods involved in data fusion of various sensors on low-altitude platforms are mentioned.

Key words: image matching, low-altitude photogrammetry, feature extraction, deep learning

中图分类号:

P237

陈晓勇, 何海清, 周俊超, 安谱阳, 陈婷. 低空摄影测量立体影像匹配的现状与展望[J]. 测绘学报, 2019, 48(12): 1595-1603.

CHEN Xiaoyong, HE Haiqing, ZHOU Junchao, AN Puyang, CHEN Ting. Progress and future of image matching in low-altitude photogrammetry[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12): 1595-1603.

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