A Bilinear–Bilinear Nonnegative Matrix Factorization Method for Hyperspectral Unmixing

Olivier Eches (1) , Mireille Olwen Guillaume (1)

1 HIPE - HIPE

Spectral unmixing of hyperspectral images consists of estimating pure material spectra with their corresponding proportions (or abundances). Non-linear modelisation of spectral unmixing problem is of very recent interest within the signal and image processing community. This letter proposes a new non-linear unmixing approach using Fan bilinear-bilinear model and non-negative matrix factorization method that takes into account physical constraints on spectra (positivity) and abundances (positivity and sum-to-one). The proposed method is tested using a projected Gradient algorithm on synthetic and real data. The performances of this method are compared to linear approach and to recent non-linear approach.

Mots clés: Hyperspectral image processing; Unmixing problem; non linear

Domaines: Traitement du signal et de l'image [eess.SP]

Olivier Eches, Mireille Olwen Guillaume. A Bilinear–Bilinear Nonnegative Matrix Factorization Method for Hyperspectral Unmixing. IEEE Geoscience and Remote Sensing Letters, 2014, 11 (4), pp.778 - 782 / ISSN 1545-598X ⟨10.1109/LGRS.2013.2278993⟩. ⟨hal-01279618⟩