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

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Academic year: 2020

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Figure

Fig. 1 Illuminated manuscripts. These two illuminated manuscripts show large and non‑homogeneous damaged areas, mainly removal of gold leaves, see “Retrieving missing contents via image inpainting” section for more details
Fig. 2 First step in the detection of the damaged regions. This detection is based on the Chan‑Vese segmentation described in “Chan‑Vese segmentation” section
Fig. 3 Second step in the detection of the damaged region. The k‑means clustering algorithm is run on the whole image selection in terms of intensity‑based image features, cf
Fig. 4 Inpainting of damaged areas in Fig. 2. Once the inpainting domain is detected, the TV inpainting model (5, 6) is used to provide a good initialisation for the exemplar‑based model (7)
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