激光雷达数据压缩的挑战和困难

M. Abdelwahab, W. El-Deeb, A. Youssif
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引用次数: 3

摘要

机载光探测与测距(LIDAR)系统应用于军事、农业、地质、交通等诸多领域。激光雷达数据采集消耗了系统存储容量中的几个gb。因此,降低车载存储容量和传输速率是必要的。压缩激光雷达数据意味着减少表示激光雷达系统获取的数字数据所需的数据量。这是通过消除数据冗余来实现压缩的。本文介绍了激光雷达系统的原理和组成,比较了有损和无损压缩技术,讨论了激光雷达数据的压缩技术,以便为激光雷达系统选择一种压缩比高、处理时间合适的压缩技术。在大多数激光雷达数据压缩技术中,激光雷达数据分类是一个重要的问题,是简化数据的预处理步骤。使用多种压缩算法增加了压缩比,但也增加了处理时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LIDAR Data Compression Challenges and Difficulties
Airborne light detection and ranging (LIDAR) system uses in many field such as military, agriculture, geology and transportation. LIDAR data acquisition consumes several gigabytes from the storage capacity of the system. So, it's necessary to reduce the on board storage capacity as well as its transmission rate. Compression of LIDAR data means reducing the amount of data required to represent the digital data acquired by LIDAR system. This is done by removing data redundancies to achieve compression. In this paper we explain LIDAR system theory and component, compare between lossy and lossless compression techniques then we discuss LIDAR data compression techniques in order to choose a suitable one for LIDAR system that gives high compression ratio with suitable processing time. In most LIDAR data compression techniques classification of LIDAR data is an important issue as a preprocessing step to simplify the data. Using more than one compression algorithms increase the compression ratio but increase the processing time as well.
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