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Lossless Compression of Multi-View Cultural Heritage Image Data

Buelow, Max von ; Guthe, Stefan ; Ritz, Martin ; Santos, Pedro ; Fellner, Dieter W. (2019)
Lossless Compression of Multi-View Cultural Heritage Image Data.
17th Eurographics Workshop on Graphics and Cultural Heritage (GCH'19). Sarajevo, Bosnia and Herzegovina (06.11.2019-09.11.2019)
doi: 10.2312/gch.20191343
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Photometric multi-view 3D geometry reconstruction and material capture are important techniques for cultural heritage digitalization. Capturing images of artifacts with high resolution and high dynamic range and the possibility to store them losslessly enables future proof application of this data. As the images tend to consume immense amounts of storage, compression is essential for long time archiving. In this paper, we present a lossless image compression approach for multi-view and material reconstruction datasets with a strong focus on data created from cultural heritage digitalization. Our approach achieves compression rates of 2:1 compared against an uncompressed representation and 1.24:1 when compared against Gzip.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2019
Autor(en): Buelow, Max von ; Guthe, Stefan ; Ritz, Martin ; Santos, Pedro ; Fellner, Dieter W.
Art des Eintrags: Bibliographie
Titel: Lossless Compression of Multi-View Cultural Heritage Image Data
Sprache: Englisch
Publikationsjahr: 2019
Verlag: Eurographics Association
Buchtitel: Eurographics Workshops and Symposia
Veranstaltungstitel: 17th Eurographics Workshop on Graphics and Cultural Heritage (GCH'19)
Veranstaltungsort: Sarajevo, Bosnia and Herzegovina
Veranstaltungsdatum: 06.11.2019-09.11.2019
DOI: 10.2312/gch.20191343
Kurzbeschreibung (Abstract):

Photometric multi-view 3D geometry reconstruction and material capture are important techniques for cultural heritage digitalization. Capturing images of artifacts with high resolution and high dynamic range and the possibility to store them losslessly enables future proof application of this data. As the images tend to consume immense amounts of storage, compression is essential for long time archiving. In this paper, we present a lossless image compression approach for multi-view and material reconstruction datasets with a strong focus on data created from cultural heritage digitalization. Our approach achieves compression rates of 2:1 compared against an uncompressed representation and 1.24:1 when compared against Gzip.

Freie Schlagworte: Image compression, Cultural heritage, Wavelet transformation
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 09 Apr 2020 12:51
Letzte Änderung: 04 Feb 2022 12:39
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