This paper addresses the problem of unmixing hyperspectral images, when the light suffers multiple interactions among distinct endmembers. In these scenarios, linear unmixing has poor accuracy since the multiple light scattering effects are not accounted for by the linear mixture model. Herein, a nonlinear scenario composed by a single layer of vegetation above the soil is considered. For this class of scene, the adopted mixing model, takes into account the second-order scattering interactions. Higher order interactions are assumed negligible. A semi-supervised unmixing method is proposed and evaluated with simulated and real hyperspectral data sets.

Date Published: 28 September 2009
PDF: 8 pages
Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770I (28 September 2009); doi: 10.1117/12.830492

Published in SPIE Proceedings Vol. 7477:
Image and Signal Processing for Remote Sensing XV
Lorenzo Bruzzone; Claudia Notarnicola; Francesco Posa, Editor(s)