AIRBORNE LIDAR POINTS CLASSIFICATION BASED ON TENSOR SPARSE REPRESENTATION

AIRBORNE LIDAR POINTS CLASSIFICATION BASED ON TENSOR SPARSE REPRESENTATION

The common statistical methods for supervised classification usually require a large amount of training data to achieve reasonable results, which is time consuming and inefficient. This paper proposes a tensor sparse representation classification (SRC) method for airborne LiDAR points. The LiDAR p...

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Bibliographic Details
Main Authors:	N. Li, N. Pfeifer, C. Liu
Format:	Article
Language:	English
Published:	Copernicus Publications 2017-09-01
Series:	ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:	https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W4/107/2017/isprs-annals-IV-2-W4-107-2017.pdf

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