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

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dc.contributor.authorBuelow, Max vonen_US
dc.contributor.authorTausch, Reimaren_US
dc.contributor.authorKnauthe, Volkeren_US
dc.contributor.authorWirth, Tristanen_US
dc.contributor.authorGuthe, Stefanen_US
dc.contributor.authorSantos, Pedroen_US
dc.contributor.authorFellner, Dieter W.en_US
dc.contributor.editorSpagnuolo, Michela and Melero, Francisco Javieren_US
dc.date.accessioned2020-11-17T17:51:37Z
dc.date.available2020-11-17T17:51:37Z
dc.date.issued2020
dc.description.abstractCultural 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.en_US
dc.description.sectionheadersVirtual/Augmented Reality and Image Processing
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.identifier.doi10.2312/gch.20201294
dc.identifier.isbn978-3-03868-110-6
dc.identifier.issn2312-6124
dc.identifier.pages71-77
dc.identifier.urihttps://doi.org/10.2312/gch.20201294
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20201294
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectImage compression
dc.subjectImage segmentation
dc.subjectImage representations
dc.titleSegmentation-Based Near-Lossless Compression of Multi-View Cultural Heritage Image Dataen_US
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GCH 2020 - Eurographics Workshop on Graphics and Cultural Heritage