Accelerated Shearlet-Domain Light Field Reconstruction

Suren Vagharshakyan, Robert Bregovic, Atanas Gotchev

    Research output: Contribution to journalArticleScientificpeer-review

    23 Citations (Scopus)
    150 Downloads (Pure)

    Abstract

    We consider the problem of reconstructing densely sampled light field (DSLF) from sparse camera views. In our previous work, the DSLF has been reconstructed by processing epipolar-plane images (EPI) employing sparse regularization in shearlet transform domain. With the aim to avoid redundant processing and reduce the overall reconstruction time, in this article we propose algorithm modifications in three directions. First, we modify the basic algorithm by offering a faster and more stable iterative procedure. Second, we elaborate on the proper use of color redundancy by studying the effect of reconstruction of an average intensity channel and its use as a guiding mode for colorizing the three color channels. Third, we explore similarities between EPIs by their grouping and joint processing or by effective decorrelation to get an initial estimate for the basic iterative procedure. We are specifically interested in GPU-based computations allowing an efficient implementation of the shearlet transform. We quantify our three main approaches to accelerated processing over a wide collection of horizontal- as well as full-parallax datasets.
    Original languageEnglish
    Number of pages10
    JournalIEEE Journal of Selected Topics in Signal Processing
    Volume11
    Issue number7
    Early online date11 Aug 2017
    DOIs
    Publication statusPublished - 2017
    Publication typeA1 Journal article-refereed

    Publication forum classification

    • Publication forum level 2

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