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

von Buelow, Max and Tausch, Reimar and Knauthe, Volker and Wirth, Tristan and Guthe, Stefan and Santos, Pedro and Fellner, Dieter W. (2020):
Segmentation-Based Near-Lossless Compression of Multi-View Cultural Heritage Image Data.
In: Eurographics Workshops and Symposia, pp. 71-77,
The Eurographics Association, GCH 2020 - Eurographics Workshop on Graphics and Cultural Heritage, virtual Conference, 18.-19.11., ISBN 978-3-03868-110-6,
DOI: 10.2312/gch.20201294,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: von Buelow, Max and Tausch, Reimar and Knauthe, Volker and Wirth, Tristan and Guthe, Stefan and Santos, Pedro and Fellner, Dieter W.
Title: Segmentation-Based Near-Lossless Compression of Multi-View Cultural Heritage Image Data
Language: English
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.

Title of Book: Eurographics Workshops and Symposia
Publisher: The Eurographics Association
ISBN: 978-3-03868-110-6
Uncontrolled Keywords: Image compression, Cultural heritage
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: GCH 2020 - Eurographics Workshop on Graphics and Cultural Heritage
Event Location: virtual Conference
Event Dates: 18.-19.11.
Date Deposited: 16 Dec 2020 08:02
DOI: 10.2312/gch.20201294
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