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Time-Frequency Analysis and Representations of the Discrete Heisenberg Group Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Approaches for Characterizing Nonlinear Mixtures in Hyperspectral Imagery

Authors : Robert S. Rand, Ronald G. Resmini, David W. Allen

Published in: Excursions in Harmonic Analysis, Volume 5

Publisher: Springer International Publishing

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Abstract

This study considers a physics-based and a kernel-based approach for characterizing pixels in a scene that may be linear (areal mixed) or nonlinear (intimately mixed). The physics-based method is based on earlier studies that indicate nonlinear mixtures in reflectance space are approximately linear in albedo space. The approach converts reflectance to single scattering albedo (SSA) according to Hapke theory assuming bidirectional scattering at nadir look angles and uses a constrained linear model on the computed albedo values. The kernel-based method is motivated by the same idea, but uses a kernel that seeks to capture the linear behavior of albedo in nonlinear mixtures of materials. The behavior of the kernel method is dependent on the value of a parameter, gamma. Validation of the two approaches is performed using laboratory data.

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Metadata
Title
Approaches for Characterizing Nonlinear Mixtures in Hyperspectral Imagery
Authors
Robert S. Rand
Ronald G. Resmini
David W. Allen
Copyright Year
2017
Book
Excursions in Harmonic Analysis, Volume 5

Print ISBN: 978-3-319-54710-7

Electronic ISBN: 978-3-319-54711-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-54711-4_5

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