Super-resolution of hyperspectral images using local spectral unmixing

Giorgio Antonino Licciardi (1) , Miguel Angel Veganzones (1) , Miguel Simoes (1, 2) , José M. Bioucas-Dias (2) , Jocelyn Chanussot (3, 1)

1 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
2 Instituto de Telecomunicações [Lisboa, Portugal]
3 University of Iceland [Reykjavik]

For many remote sensing applications it is preferable to have images with both high spectral and spatial resolutions. On this regards, hyperspectral and multispectral images have complementary characteristics in terms of spectral and spatial resolutions. In this paper we propose an approach for the fusion of low spatial resolution hyperspectral images with high spatial resolution multispectral images in order to obtain superresolution (spatial and spectral) hyperspectral images. The proposed approach is based on the assumption that, since both hyperspectral and multispectral images acquired on the same scene, the corresponding endmembers should be the same. On a first step the hyperspectral image is spectrally downsampled in order to match the multispectral one. Then an endmember extraction algorithm is performed on the downsampled hyperspectral image and the successive abundance estimation is performed on the multispectral one. Finally, the extracted endmembers are up-sampled back to the original hyperspectral space and then used to reconstruct the super-resolution hyperspectral image according to the abundances obtained from the multispectral image.

Mots clés: Hyperspectral imaging; super-resolution; spectral unmixing

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

Giorgio Antonino Licciardi, Miguel Angel Veganzones, Miguel Simoes, José M. Bioucas-Dias, Jocelyn Chanussot. Super-resolution of hyperspectral images using local spectral unmixing. WHISPERS 2014 - 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Jun 2014, Lausanne, Switzerland. pp.n/c. ⟨hal-01010428⟩