Title :
Joint linear/nonlinear spectral unmixing of hyperspectral image data
Author :
Plaza, Javier ; Plaza, Antonio ; Pérez, Rosa ; Martínez, Pablo
Author_Institution :
Univ. of Extremadura, Caceres
Abstract :
Many available techniques for spectral mixture analysis involve the separation of mixed pixel spectra collected by imaging spectrometers into pure component (endmember) spectra, and the estimation of abundance values for each end- member. Although linear mixing models generally provide a good abstraction of the mixing process, several naturally occurring situations exist where nonlinear models may provide the most accurate assessment of endmember abundance. In this paper, we propose a combined linear/nonlinear mixture model which makes use of linear mixture analysis to provide an initial model estimation, which is then thoroughly refined using a multi-layer neural network coupled with intelligent algorithms for automatic selection of training samples. Three different algorithms for automatic selection of training samples, such as border training algorithm (BTA), mixed signature algorithm (MSA) and mophological erosion algorithm (MEA) are developed for this purpose. The proposed model is evaluated in the context of a real application which involves the use of hyperspectral data sets, collected by the Digital Airborne (DAIS 7915) and Reflective Optics System (ROSIS) imaging spectrometers of DLR, operating simultaneously at multiple spatial resolutions.
Keywords :
geophysics computing; image processing; neural nets; remote sensing; spectral analysis; DAIS 7915; DLR; ROSIS; border training algorithm; digital airborne imaging spectrometers; hyperspectral image data; linear mixing model; mixed signature algorithm; mophological erosion algorithm; multilayer neural network; reflective optics system imaging spectrometers; spectral mixture analysis; spectral unmixing; Algorithm design and analysis; Coupled mode analysis; Couplings; Hyperspectral imaging; Image analysis; Multi-layer neural network; Optical imaging; Pixel; Spectral analysis; Spectroscopy;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4423735