2020 Impact factor 2.707
Special Topics

EPJ Plus Focus Point Issue: Advances in Hyperspectral Data Processing for Cultural Heritage

Aims and Goals

This Focus Point invites contributions that showcase the most recent advances in the processing of close-range hyperspectral data of Cultural Heritage assets.

Technological improvements in spectroscopic imaging are leading to the necessity of relying more and more on computational approaches for processing large amounts of data in order to maximise the extraction of information and provide quantitative results. This is becoming increasingly relevant also in the domain of Cultural Heritage, where hyperspectral imaging methods are progressively acquiring more relevance for the analysis of artworks and antiquities held at Galleries, Libraries, Archives and Museums (GLAM).

Rather than on data acquisition or instrumental advances, papers to be included in this collection should focus on illustrating computational approaches that can be adopted to improve the quality of the images (e.g., noise removal, super-resolution, spectral unmixing etc.) and maximise the granularity of the results. Studies related to Machine Learning approaches for automatic classification, pattern recognition and multivariate clustering are particularly welcomed.

The Focus Point accepts also contributions on image processing approaches developed in other disciplines (e.g., medical imaging) that might be transferred to the field of Cultural Heritage and used for the study of cultural assets even if not tested yet, as long as the potential migration of techniques is sufficiently supported by clear motivations.

Overall, the Focus Point will include topic such as (but not limited to):

  • Image processing methods for hyperspectral data (including image enhancement)
  • Computational approaches for automatic classification, pattern recognition and multivariate clustering
  • Machine Learning techniques for automating processes of analysis (e.g. automatic pigments identification)
  • Examples on hidden image retrieval based on irregularity detection
  • Technology transfer in hyperspectral image processing from other domains to Cultural Heritage

Authors are encouraged to submit contributions in the form of research papers, or short reviews. Manuscripts should be prepared following the instructions for authors using the latex template of EPJ Plus, which can be downloaded here. Articles should be submitted to the Editorial Office of EPJ Plus via the submission system at http://www.editorialmanager.com/epjp by replying "yes" to the question 'Are you submitting this manuscript following an invitation to contribute to a "focus point" (topical article collection by invitation of guest editors)?' and then selecting “Focus Point on Advances in Hyperspectral Data Processing for Cultural Heritage. Guest editors: A. Traviglia, A. Artesani, M. Fiorucci, M. Ljubenovic".

Submission Deadline: October 31, 2021.

We are looking forward to your contributions.

Guest Editors:

Arianna Traviglia
Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia
Venice, Italy, E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Alessia Artesani
Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia
Venice, Italy, E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Marco Fiorucci
Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia
Venice, Italy, E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Marina Ljubenovic
Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia
Venice, Italy, E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Open Access: EPJ Plus is a hybrid journal offering Open Access publication via the Open Choice programme and a growing number of Springer Compact “Publish and Read” arrangements which enable authors to publish OA at no direct cost (all costs are paid centrally).

Managing Editors
Anne Ruimy and Vijala Kiruvanayagam (EDP Sciences) and Sabine Lehr (Springer-Verlag)
Dear Sabine, Sandrine, and Nicolas, your professional and efficient management supported our editing tasks enormously and made the whole process smooth and pleasant. The web-based SAGA system was very helpful for handling the workflow. Thank you all for your high commitment!

Jan Freund, ICBM, University of Oldenburg, Germany

ISSN: 1951-6355 (Print Edition)
ISSN: 1951-6401 (Electronic Edition)

© EDP Sciences and Springer-Verlag