Lossless Compression of Multi-View Cultural Heritage Image Data

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.