Sharpening Hyperspectral Images Using Plug-and-Play Priors

  • Afonso Teodoro
  • José Bioucas-Dias
  • Mário Figueiredo
Conference paper

DOI: 10.1007/978-3-319-53547-0_37

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10169)
Cite this paper as:
Teodoro A., Bioucas-Dias J., Figueiredo M. (2017) Sharpening Hyperspectral Images Using Plug-and-Play Priors. In: Tichavský P., Babaie-Zadeh M., Michel O., Thirion-Moreau N. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2017. Lecture Notes in Computer Science, vol 10169. Springer, Cham

Abstract

This paper addresses the problem of fusing hyperspectral (HS) images of low spatial resolution and multispectral (MS) images of high spatial resolution into images of high spatial and spectral resolution. By assuming that the target image lives in a low dimensional subspace, the problem is formulated with respect to the latent representation coefficients. Our major contributions are: (i) using patch-based spatial priors, learned from the MS image, for the latent images of coefficients; (ii) exploiting the so-called plug-and-play approach, wherein a state-of-the-art denoiser is plugged into the iterations of a variable splitting algorithm.

Keywords

Data fusion Hyperspectral imaging Multispectral imaging Latent variables Plug-and-play Gaussian mixtures 

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Afonso Teodoro
    • 1
    • 2
  • José Bioucas-Dias
    • 1
    • 2
  • Mário Figueiredo
    • 1
    • 2
  1. 1.Instituto de TelecomunicaçõesLisbonPortugal
  2. 2.Instituto Superior Técnico, Universidade de LisboaLisbonPortugal

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