Hierarchical beta process with gaussian process prior for hyperspectral image super resolution

    Research output: Chapter in Book/Conference paperConference paperpeer-review

    39 Citations (Scopus)
    10 Downloads (Pure)


    © Springer International Publishing AG 2016.Hyperspectral cameras acquire precise spectral information, however, their resolution is very low due to hardware constraints.We propose an image fusion based hyperspectral super resolution approach that employes a Bayesian representation model. The proposed model accounts for spectral smoothness and spatial consistency of the representation by using Gaussian Processes and a spatial kernel in a hierarchical formulation of the Beta Process. The model is employed by our approach to first infer Gaussian Processes for the spectra present in the hyperspectral image. Then, it is used to estimate the activity level of the inferred processes in a sparse representation of a high resolution image of the same scene. Finally, we use the model to compute multiple sparse codes of the high resolution image, that are merged with the samples of the Gaussian Processes for an accurate estimate of the high resolution hyperspectral image. We perform experiments with remotely sensed and ground-based hyperspectral images to establish the effectiveness of our approach.
    Original languageEnglish
    Title of host publicationComputer Vision – ECCV 2016. ECCV 2016. Lecture Notes in Computer Science
    EditorsBastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
    Place of PublicationSwitzerland
    Number of pages18
    ISBN (Print)9783319464862
    Publication statusPublished - 2016
    Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
    Duration: 8 Oct 201616 Oct 2016

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9907 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference14th European Conference on Computer Vision, ECCV 2016


    Dive into the research topics of 'Hierarchical beta process with gaussian process prior for hyperspectral image super resolution'. Together they form a unique fingerprint.

    Cite this