A quantitative and comparative analysis of linear and nonlinear spectral mixture models using radial basis function neural networks

IEEE Transactions on Geoscience and Remote Sensing

Volumn 39, Issue 10, 2001, Pages 2314-2318

  Guilfoyle, Kerri J ^b   Althouse, Mark L ^a,b   Chang, Chein I ^a,b  

^a IEEE   (United States)

^b Baltimore County   (United States)

Author keywords

Linear mixture; Nonlinear mixture; Radial basis function neural network (RBFNN)

Indexed keywords

SPECTRAL MIXTURES;

IMAGE ANALYSIS; MATHEMATICAL MODELS; RADIAL BASIS FUNCTION NETWORKS; SPECTROMETERS; SPECTRUM ANALYSIS;

IMAGING SYSTEMS;

EID: 0035481565     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.957296     Document Type: Article

References (6)

1. Photometric phase functions of common geologic minerals and applications to quantitative analysis of mineral mixture reflectance spectra
2. Bidirectional reflectance spectroscopy, 1, theory
3. Spectral mixture modelling for spatially distinct and randomly distributed regions
4. Simple algorithms for remote determination of mineral abundances and particle sizes from reflectance spectra
5. Array processing using radial basis function neural network