Rand, R.
, Resmini, R.
and Allen, D.
(2017),
Approaches for Characterizing Nonlinear Mixtures in Hyperspectral Imagery, Excursions in Harmonic Analysis, Springer International Publishing AG, CH-6330 Cham (ZG), ME, [online], https://doi.org/10.1007/978-3-319-54711-4_5
(Accessed September 8, 2024)
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Approaches for Characterizing Nonlinear Mixtures in Hyperspectral Imagery
Published
Author(s)
Robert S. Rand, Ronald G. Resmini,
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.Citation
Excursions in Harmonic Analysis
Publisher Info
Springer International Publishing AG, CH-6330 Cham (ZG), ME
Pub Type
Book Chapters
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Keywords
Nonlinear mixtures, Kernel-based methods, Single scattering albedo, Hapke theory, Hyperspectral
Citation
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Created June 20, 2017, Updated October 12, 2021