Hyper-Hue and EMAP on Hyperspectral Images for Supervised Layer Decomposition of Old Master Drawings

Davari A, Sakaltras N, Haeberle A, Vesal S, Christlein V, Maier A, Riess C (2018)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2018

Publisher: IEEE Computer Society

Book Volume: abs/1801.09472

Pages Range: tbd

Conference Proceedings Title: International Conference on Image Processing (ICIP)

Event location: Athens, Greece

ISBN: 9781479970612

URI: http://arxiv.org/abs/1801.09472

DOI: 10.1109/ICIP.2018.8451768

Abstract

Old master drawings were mostly created step by step in several layers using different materials. To art historians and restorers, examination of these layers brings various insights into the artistic work process and helps to answer questions about the object, its attribution and its authenticity. However, these layers typically overlap and are oftentimes difficult to differentiate with the unaided eye. For example, a common layer combination is red chalk under ink. In this work, we propose an image processing pipeline that operates on hyperspectral images to separate such layers. In particular, we propose to use two descriptors in hyperspectral historical document analysis, namely hyper-hue and extended multi-attribute profile (EMAP). We show that hyperspectral images enable better layer separation than RGB images, and that spectral focus stacking is an important preprocessing step towards that goal. Our comparative results with other features underline the efficacy of the three proposed improvements.

Authors with CRIS profile

How to cite

APA:

Davari, A., Sakaltras, N., Haeberle, A., Vesal, S., Christlein, V., Maier, A., & Riess, C. (2018). Hyper-Hue and EMAP on Hyperspectral Images for Supervised Layer Decomposition of Old Master Drawings. In International Conference on Image Processing (ICIP) (pp. tbd). Athens, Greece: IEEE Computer Society.

MLA:

Davari, Amirabbas, et al. "Hyper-Hue and EMAP on Hyperspectral Images for Supervised Layer Decomposition of Old Master Drawings." Proceedings of the International Conference on Image Processing (ICIP), Athens, Greece IEEE Computer Society, 2018. tbd.

BibTeX: Download