Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 21, Issue 6, Pages 3017-3025Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2012.2187668
Keywords
Hyperspectral imagery; postnonlinear model; spectral unmixing (SU)
Funding
- Direction Generale de l'Armement, French Ministry of Defense
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This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated using polynomial functions leading to a polynomial postnonlinear mixing model. A Bayesian algorithm and optimization methods are proposed to estimate the parameters involved in the model. The performance of the unmixing strategies is evaluated by simulations conducted on synthetic and real data.
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