An efficient approach for multi-temporal hyperspectral images interpretation based on high-order tensor

Salim Hemissi (1, 2) , Imed Riadh Farah (1, 2) , Karim Saheb Ettabaa (1, 2) , Basel Solaiman (1)

1 ITI - Département Image et Traitement Information
2 RIADI - Laboratoire de recherche en Génie Logiciel, Applications distribuées, Systèmes décisionnels et Imagerie intelligente [Manouba]

The main purpose of this paper is to propose and to validate a new multi-temporal algorithm for hyperspectral endmembers extraction. The advanced approach is based on multi-linear algebra, spectral analysis and tensor data structure for each pixel. The detection of an endmember in the time series is done by the interpretation of the spatial-temporal signature in a multi-dimensional tonsorial space. Thus, the images could have different resolutions and could be coming from different dates. A multi-temporal synthetic and Hyperion series images were used to assess the effectiveness of the proposed algorithm. The obtained results show good performances with both permanent and temporal known features.

Salim Hemissi, Imed Riadh Farah, Karim Saheb Ettabaa, Basel Solaiman. An efficient approach for multi-temporal hyperspectral images interpretation based on high-order tensor. Proceedings of SPIE, the International Society for Optical Engineering, 2011, 8180, pp.81800J-81800J-6. ⟨10.1117/12.898015⟩. ⟨hal-00795109⟩