Title :
A sparsity promoting bilinear unmixing model
Author :
Gader, Paul ; Dranishnikov, Dmitri ; Zare, Alina ; Chanussot, Jocelyn
Author_Institution :
Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
An algorithm, Bilinear SPICE (BISPICE), for simultaneously estimating the number of endmembers, the endmembers, and proportions for a bilinear mixing model is derived and evaluated. BISPICE generalizes the SPICE algorithm for linear mixing. The proportion estimation steps of SPICE and BISPICE are similar. However, the endmember updates, one novel aspect of the work, are quite different. The SPICE objective function is quadratic in the endmembers. The BISPICE is a fourth degree polynomial. In SPICE, endmembers are updated simultaneously via a closed form. In BISPICE, each endmember must be updated with respect to all other endmembers. Empirically, BISPICE estimated endmembers and proportions more accurately then SPICE, even though the data fitting error was higher.
Keywords :
geophysical image processing; hyperspectral imaging; BISPICE algorithm; SPICE objective function; bilinear SPICE algorithm; data fitting error; endmember estimation; fourth degree polynomial; linear mixing; sparsity promoting bilinear unmixing model; Computational modeling; Hyperspectral imaging; Ice; Linear programming; SPICE; Signal processing; Signal processing algorithms;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2012 4th Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3405-8
DOI :
10.1109/WHISPERS.2012.6874255