期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 1
出版社：Copernicus Publications
摘要：Today’s advanced LiDAR systems are able to record the entire laser echo pulse, provided that sufficient data storage is available onthe airborne platform. The recorded echo pulses, frequently called waveform data or full-waveform, can then be used to analyze theproperties of the reflecting surface, such as classifying objects based on their material signatures; for example, land classification.However, both the efficient storage of waveform data and the waveform-based classification still present formidable challenges. Inthis paper, solutions based on state-of-the-art numerical methods, including the Discrete Wavelet Transform and Kohonen’s Self-Organizing Map, are proposed to carry out these tasks. Using the Discrete Wavelet Transform has two advantages: first, it is anefficient tool to compress waveform data, and second, the wavelet coefficients describe the shape of the echo pulse, and, therefore,they can also be used for classification. The performance of the proposed method is evaluated using actual waveform data
