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Unveiling the invisible: mathematical methods for restoring and interpreting illuminated manuscripts.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Calatroni, Luca 
d'Autume, Marie 
Hocking, Rob 
Panayotova, Stella 
Parisotto, Simone 

Abstract

The last 50 years have seen an impressive development of mathematical methods for the analysis and processing of digital images, mostly in the context of photography, biomedical imaging and various forms of engineering. The arts have been mostly overlooked in this process, apart from a few exceptional works in the last 10 years. With the rapid emergence of digitisation in the arts, however, the arts domain is becoming increasingly receptive to digital image processing methods and the importance of paying attention to this therefore increases. In this paper we discuss a range of mathematical methods for digital image restoration and digital visualisation for illuminated manuscripts. The latter provide an interesting opportunity for digital manipulation because they traditionally remain physically untouched. At the same time they also serve as an example for the possibilities mathematics and digital restoration offer as a generic and objective toolkit for the arts.

Description

Keywords

3D visualisation, Image inpainting, Image osmosis, Mathematical image reconstruction, Sample

Journal Title

Herit Sci

Conference Name

Journal ISSN

2050-7445
2050-7445

Volume Title

6

Publisher

Springer Science and Business Media LLC
Sponsorship
EPSRC (1513548)
Engineering and Physical Sciences Research Council (EP/N014588/1)
Engineering and Physical Sciences Research Council (EP/M00483X/1)
Engineering and Physical Sciences Research Council (EP/J009539/1)
Engineering and Physical Sciences Research Council (EP/L016516/1)
Arts and Humanities Research Council (AH/R001545/1)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (777826)
Luca Calatroni acknowledges the support of Fondation Mathémathique Jacques Hadamard (FMJH). Simone Parisotto acknowledges the UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/L016516/1 for the University of Cambridge Centre for Doctoral Training, the Cambridge Centre for Analysis. Carola-Bibiane Schöenlieb acknowledges support from the Engineering and Physical Sciences Research Council (EPSRC) ’EP/K009745/1’, the Leverhulme Trust project ’Breaking the non-convexity barrier’, the EPSRC grant ’EP/M00483X/1’, the EPSRC centre ’EP/N014588/1’, the Alan Turing Institute ’TU/B/000071’, CHiPS (Horizon 2020 RISE project grant), the Isaac Newton Institute, and the Cantab Capital Institute for the Mathematics of Information