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

Maximilian von Bülow, Reimar Tausch, Volker Knauthe, Tristan Wirth, Stefan Guthe, Pedro Santos, Dieter W. Fellner

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


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.
Original languageEnglish
Title of host publicationEurographics Workshop on Graphics and Cultural Heritage (GCH 2020)
EditorsMichela Spagnuolo, Francisco Javier Melero
PublisherEurographics - European Association for Computer Graphics
Number of pages7
ISBN (Print)978-3-03868-110-6
Publication statusPublished - 2020

Fields of Expertise

  • Information, Communication & Computing


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