Minimum description length constrained LiDAR waveform decomposition

Waveform decomposition is a necessary step for the exploitation of full waveform LiDAR data. Much effort has been focused on designing algorithms to decompose the waveform into a fixed number of components. However, the determination of the appropriate number of components in a waveform, though crucial, is rarely studied. This paper introduces an order identification method, Minimum Description Length (MDL) to estimate the number of components. MDL requires the addition of a penalty term in the model fitness to account for the over-fitting of high order models. The convexity of MDL in terms of the number of components makes it possible to find out optimal model with 2-4 iterations in most cases. We applied the MDL-based estimation method to analyze a dataset collected by a Riegl Q680i LiDAR system. The procedure is demonstrated in this paper.