Analysis of spectral data using spatial context

Jeremy P. Metcalf; Richard C. Olsen

doi:10.1117/12.2519187

14 May 2019 Analysis of spectral data using spatial context

Jeremy P. Metcalf, Richard C. Olsen

Proceedings Volume 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV; 1098607 (2019) https://doi.org/10.1117/12.2519187
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Spectral LiDAR analysis can be enabled by the use of spatial context, spatial structure, and prior information in the form of map data. LiDAR intensity imagery are analyzed here using an object-based approach which segments the data according to vector information obtained from OpenStreetMap and other vector map information. Polygons and features from the map vectors are used to establish regions of interest for analysis. This automates the training process for use of traditional statistical classifiers and machine learning algorithms. Map-derived objects can demonstrate multiple spectral components which must be resolved to define the primary object, and its semantic label.

Conference Presentation

Citation Download Citation

Jeremy P. Metcalf and Richard C. Olsen "Analysis of spectral data using spatial context", Proc. SPIE 10986, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, 1098607 (14 May 2019); https://doi.org/10.1117/12.2519187

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