Resumen

MARQUEZ, Miguel A.; VARGAS, Cesar A.  y  ARGUELLO, H.. Compact spatio-spectral algorithm for single image super-resolution in hyperspectral imaging. Ing. Investig. [online]. 2016, vol.36, n.3, pp.117-124. ISSN 0120-5609.  https://doi.org/10.15446/ing.investig.v36n3.54267.

Hyperspectral imaging (HSI) is used in a wide range of applications such as remote sensing, space imagery, mineral detection, and exploration. Unfortunately, it is difficult to acquire hyperspectral images with high spatial and spectral resolution due to instrument limitations. The super-resolution techniques are used to reconstruct low-resolution hyperspectral images. However, traditional super-resolution (SR) approaches do not allow direct use of both spatial and spectral information, which is a decisive for an optimal reconstruction. This paper proposes a single image SR algorithm for HSI. The algorithm uses the fact that the spatial and spectral information can be integrated to make an accurate estimate of the high-resolution HSI. To achieve this, two types of spatio-spectral downsampling, and a three-dimensional interpolation are proposed in order to increase coherence between the spatial and spectral information. The resulting reconstructions using the proposed method are up to 2 dB better than traditional SR approaches.

Palabras clave : Hyperspectral imaging; spatio-spectral dimension; three-dimensional interpolation; hyperspectral downsampling.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )