Published

2016-09-01

Compact spatio-spectral algorithm for single image super-resolution in hyperspectral imaging

Superresolución basado en una única imagen para imágenes hiperespectrales

Keywords:

Hyperspectral imaging, spatio-spectral dimension, three-dimensional interpolation, hyperspectral downsampling (en)
Imágenes hiperespectrales, dimensión especial-espectral, interpolación tridimensional, sub-muestreo hiperespectral (es)

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Authors

  • Miguel Angel Marquez Castellanos Universidad Industrial de Santander, Colombia.
  • Cesar Augusto Vargas Ph.D student at University of Delaware, USA.
  • Henry Arguello Associated professor at Universidad Industrial de Santander, Colombia.

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 superresolution (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- pectral 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.

Las imágenes hiperespectrales (HSI) son de vital importancia en una amplia gama de aplicaciones, tales como la teledetección, imágenes espaciales, la detección y la exploración de minerales. Desafortunadamente, es difícil adquirir HSI de alta resolución espacio-espectral debido a las limitaciones de los equipos de sensado. Para obtener versiones de HSI de alta calidad se usan técnicas tradicionales de superresolución. Éstas técnicas no permiten el uso directo de la información espacial y espectral que son un factor decisivo para una óptima reconstrucción. En este trabajo se propone la implementación de un novedoso algoritmo de superresolución de una sola imagen hiperespectral. El algoritmo integra la información espacial y espectral en las HSI para realizar una estimación precisa de alta resolución. Esta integración se obtiene mediante el uso de dos tipos de muestreo espacio-espectral y un interpolador tridimensional, que permite aumentar la coherencia de la información inherente en la imagen. Las imágenes resultantes son superiores hasta 2 dB comparas con reconstrucciones obtenidas por enfoques tradicionales.

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Copyright (c) 2016 Miguel Angel Marquez Castellanos, Cesar Augusto Vargas, Henry Arguello

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