On-Line Blind Unmixing For Hyperspectral Pushbroom Imaging Systems

Ludivine Nus, Sebastian Miron, David Brie
2018 2018 IEEE Statistical Signal Processing Workshop (SSP)  
In this paper, the on-line hyperspectral image blind unmixing is addressed. Inspired by the Incremental Non-negative Matrix Factorization (INMF) method [2], we propose an on-line NMF which is adapted to the acquisition scheme of a pushbroom imager. Because of the non-uniqueness of the NMF model, a minimum volume constraint on the endmembers is added allowing to reduce the set of admissible solutions. This results in a stable algorithm yielding results similar to those of standard off-line NMF
more » ... dard off-line NMF methods, but drastically reducing the computation time. The algorithm is applied to wood hyperspectral images showing that such a technique is effective for the on-line prediction of wood piece rendering after finishing. Index Terms-Hyperspectral imaging, Pushbroom imager, On-line Non-negative Matrix Factorization, Minimum volume constraint.
doi:10.1109/ssp.2018.8450702 dblp:conf/ssp/NusMB18 fatcat:pfhyq4x66vad7ldhw25bhc5muq