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The Art of Inpainting

The Art of Inpainting

The Art of Inpainting

Mathematical Methods for the Virtual Restoration of Illuminated Manuscripts
Simone Parisotto, Fitzwilliam Museum, Cambridge
Patricia Vitoria, Universitat Pompeu Fabra, Barcelona
Coloma Ballester, Universitat Pompeu Fabra, Barcelona
Aurélie Bugeau, Université de Bordeaux
Suzanne Reynolds, Fitzwilliam Museum, Cambridge
Carola-Bibiane Schönlieb, University of Cambridge
July 2025
Hardback
9781009585941
$99.99
USD
Hardback

    The art of image restoration and completion has entered a new phase thanks to digital technology. Indeed, virtual restoration is sometimes the only feasible option available to us, and it has, under the name 'inpainting', grown, from methods developed in the mathematics and computer vision communities, to the creation of tools used routinely by conservators and historians working in the worlds of fine art and cinema. The aim of this book is to provide, for a broad audience, a thorough description of imaging inpainting techniques. The book has a two-layer structure. In one layer, there is a general and more conceptual description of inpainting; in the other, there are boxed descriptions of the essentials of the mathematical and computational details. The idea is that readers can easily skip those boxes without disrupting the narrative. Examples of how the tools can be used are drawn from the Fitzwilliam Museum, Cambridge collections.

    • Reviews over 100 inpainting methods, tested in the real-case scenario of the virtual restoration of manuscript illumination
    • Makes the theory accessible to readers without specialised training in inpainting
    • Provides examples of inter-disciplinary research opportunities at the intersection of maths and art
    • Expands creative possibilities for both artist and scientist by providing further theoretical tools in both contexts

    Product details

    July 2025
    Hardback
    9781009585941
    0 pages
    Not yet published - available from July 2025

    Table of Contents

    • 1. Introduction
    • 2. Local inpainting methods
    • 3. Non-local inpainting methods
    • 4. Deep learning inpainting methods
    • 5. Methods inspired from cultural heritage
    • 6. Conclusions
    • Appendix. Manuscripts in focus
    • Bibliography
    • Index.