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    Segmentation-Based Near-Lossless Compression of Multi-View Cultural Heritage Image Data

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    Date
    2020
    Author
    Buelow, Max von
    Tausch, Reimar
    Knauthe, Volker
    Wirth, Tristan
    Guthe, Stefan
    Santos, Pedro
    Fellner, Dieter W. ORCID
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    Abstract
    Cultural heritage preservation using photometric approaches received increasing significance in the past years. Capturing of these datasets is usually done with high-end cameras at maximum image resolution enabling high quality reconstruction results while leading to immense storage consumptions. In order to maintain archives of these datasets, compression is mandatory for storing them at reasonable cost. In this paper, we make use of the mostly static background of the capturing environment that does not directly contribute information to 3d reconstruction algorithms and therefore may be approximated using lossy techniques. We use a superpixel and figure-ground segmentation based near-lossless image compression algorithm that transparently decides if regions are relevant for later photometric reconstructions. This makes sure that the actual artifact or structured background parts are compressed with lossless techniques. Our algorithm achieves compression rates compared to the PNG image compression standard ranging from 1:2 to 1:4 depending on the artifact size.
    BibTeX
    @inproceedings {h.20201294,
    booktitle = {Eurographics Workshop on Graphics and Cultural Heritage},
    editor = {Spagnuolo, Michela and Melero, Francisco Javier},
    title = {{Segmentation-Based Near-Lossless Compression of Multi-View Cultural Heritage Image Data}},
    author = {Buelow, Max von and Tausch, Reimar and Knauthe, Volker and Wirth, Tristan and Guthe, Stefan and Santos, Pedro and Fellner, Dieter W.},
    year = {2020},
    publisher = {The Eurographics Association},
    ISSN = {2312-6124},
    ISBN = {978-3-03868-110-6},
    DOI = {10.2312/gch.20201294}
    }
    URI
    https://doi.org/10.2312/gch.20201294
    https://diglib.eg.org:443/handle/10.2312/gch20201294
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    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA