In this paper, we propose a compression algorithm focused on the peculiarities of hyperspectral images. The spectral redundancy in hyperspectral images is exploited by using a con...
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
This paper studies a hierarchical Bayesian model for nonlinear hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are polynomial functions of li...
Yoann Altmann, Abderrahim Halimi, Nicolas Dobigeon...
Abstract—Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or abundances) from an observed hyperspect...
An important aspect of spectral image analysis is identification of materials present in the object or scene being imaged. Enabling technologies include image enhancement, segment...
Fang Li, Michael K. Ng, Robert J. Plemmons, Sudhak...