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Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing

机译:光学影像与LiDAR点云融合在摄影测量和遥感中的研究进展

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摘要

Optical imagery and Light Detection And Ranging (LiDAR) point cloud are two major data sources in the community of photogrammetry and remote sensing. Optical images and LiDAR data have unique characteristics that make them preferable in certain applications. On the other hand, the disadvantage of one type of data source may be compensated by an advantage of the other. Hence, data fusion is a prerequisite to utilising the complementary characteristics of both data sources. Numerous methods haven been proposed to perform the fusion in various applications. This article makes a systematic review of the state-of-the-art fusion methodology used in various applications, such as registration, generation of true orthophotographs, pan-sharpening, classification, recognition of some key targets, three-dimensional reconstruction, change detection and forest inventory. Moreover, the future developing trends are introduced. In the coming few years, we expect that fusion of optical images and LiDAR point cloud will promote the development of both photogrammetry and laser scanning in both industry and scientific research.
机译:光学图像和光检测与测距(LiDAR)点云是摄影测量和遥感领域的两个主要数据源。光学图像和LiDAR数据具有独特的特性,使其在某些应用中更为可取。另一方面,一种类型的数据源的缺点可以通过另一种类型的优点来补偿。因此,数据融合是利用两个数据源的互补特性的前提。已经提出了许多方法来在各种应用中执行融合。本文对各种应用中使用的最新融合方法进行了系统的综述,例如配准,生成正射照片,锐化锐化,分类,识别一些关键目标,三维重建,变更检测和森林清单。此外,介绍了未来的发展趋势。在未来的几年中,我们预计光学图像和LiDAR点云的融合将在工业和科学研究中促进摄影测量学和激光扫描的发展。

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