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Unveiling the Invisible: Mathematical Methods for Restoring and Interpreting Illuminated Manuscripts

Penelitian - Researchers show a range of mathematical methods for digital image restoration and digital visualisation for illuminated manuscripts. The latter provide for digital manipulation, at the same time also serve for the possibilities mathematics and digital restoration offer as a generic and objective toolkit for the arts.

Medieval and Renaissance illuminated manuscripts present a particular challenge, but also an opportunity to transform current understanding of European visual culture between the 6th and 16th century. Illuminated manuscripts are the largest and best preserved resource for the study of European painting before 1500.

Penelitian Unveiling the Invisible Mathematical Methods for Restoring and Interpreting Illuminated Manuscripts

The digital processing, analysis and archiving of databases and collections in the arts and humanities is becoming increasingly important. A myriad of possibilities that digitisation opens up that go well beyond the organisation and manipulation of the actual physical objects, allowing, for instance, the creation of digital databases with respect to several parameters.

The digital processing and analysis of objects that are non-destructive to the original object, and the application of automated algorithms for sorting newly found objects into existing digital databases by classifying them into pre-defined groups in the database.

These possibilities go hand-in-hand with ever-growing advances in data science that are developing mathematical methodology for analysing and processing digital data. A large component of digital data in the arts and humanities is composed of digital images.

Despite many developments of mathematical image analysis methods in applications like biomedicine, the physical sciences and various forms of engineering, the arts and humanities have been mostly overlooked as an application in need of bespoke mathematical image analysis methods.

Researchers consider automated and semi-automated models for digital image restoration based on partial differential equations, exemplar-based image inpainting and osmosis filtering, and their translation to the digital interpretation of illuminated manuscripts.

“We refer to mathematical image processing as the task of digital image restoration or reconstruction, that is the digital processing of a given image to correct for its visual imperfections,” said Carola-Bibiane Schönlieb of the University of Cambridge in UK.

“Generally, this is done with the main intention of producing a final result where imperfections have been corrected in a visually least distracting way. This is the case for several imaging tasks such as image denoising, deblurring and also image inpainting,” Schönlieb said.

The team propose a semi-supervised approach for the segmentation of damaged areas of colour accurate images of illuminated manuscripts and for the retrieval of missing information via a two-step image inpainting model. The method present a mathematical pipeline to convert 2D painting into 3D scene by means of the construction of an appropriate depth map.

Journal : Luca Calatroni et al. Unveiling the invisible: mathematical methods for restoring and interpreting illuminated manuscripts, Heritage Science, 24 September 2018, DOI:10.1186/s40494-018-0216-z



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