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  • Data Types:
    • Other
    • Dataset
  • Supplementary Data: pages 2-12: daily mean global radiation (column 3, W/m2) pages 13-23: daily mean relative humidity (column 3, %) pages 24-34: daily mean global temperature (column 3, °C)
    Data Types:
    • Dataset
    • Document
  • Related Article: Santanu Pathak, Parnika Das, Tilak Das, Guruprasad Mandal, Boby Joseph, Manjulata Sahu, S. D. Kaushik, Vasudeva Siruguri|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|1034|doi:10.1107/S2053229620013960
    Data Types:
    • Dataset
  • Related Article: Santanu Pathak, Parnika Das, Tilak Das, Guruprasad Mandal, Boby Joseph, Manjulata Sahu, S. D. Kaushik, Vasudeva Siruguri|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|1034|doi:10.1107/S2053229620013960
    Data Types:
    • Dataset
  • Uncovering the underdrawings (UDs), the preliminary sketch made by the painter on the grounded preparatory support, is a keystone for understanding the painting's history including the original project of the artist, the pentimenti (an underlying image in a painting providing evidence of revision by the artist) or the possible presence of co-workers’ contributions. The application of infrared reflectography (IRR) has made the dream of discovering the UDs come true: since its introduction, there has been a growing interest in the technology, which therefore has evolved leading to advanced instruments. Most of the literature either report on the technological advances in IRR devices or present case studies, but a straightforward method to improve the visibility of the UDs has not been presented yet. Most of the data handling methods are devoted to a specific painting or they are not user-friendly enough to be applied by non-specialized users, hampering, thus, their widespread application in areas other than the scientific one, e.g., in the art history field. We developed a computer-assisted method, based on principal component analysis (PCA) and image processing, to enhance the visibility of UDs and to support the art-historians and curators’ work. Based on ImageJ/Fiji, one of the most widespread image analysis software, the algorithm is very easy to use and, in principle, can be applied to any multi- or hyper-spectral image data set. In the present paper, after describing the method, we accurately present the extraction of the UD for the panel “The Holy Family with St. Anne and the Young St. John” and for other four paintings by Luini and his workshop paying particular attention to the painting known as “The Child with the Lamb”.
    Data Types:
    • Collection
  • Supplemental material, sj-pdf-1-asp-10.1177_0003702820949928 for Behind the Scene of “The Holy Family with St. Anne and the Young St. John” by Bernardino Luini: A Computer-Assisted Method to Unveil the Underdrawings by Michele Caccia, Letizia Bonizzoni, Marco Martini, Raffaella Fontana, Valeria Villa and Anna Galli in Applied Spectroscopy
    Data Types:
    • Document
  • Related Article: Nicola Panza, Armando di Biase, Silvia Rizzato, Emma Gallo, Giorgio Tseberlidis, Alessandro Caselli|2020|Eur.J.Org.Chem.|2020|6635|doi:10.1002/ejoc.202001201
    Data Types:
    • Dataset
  • Related Article: Michele Fiore, Samuel Wheeler, Kevin Hurlbutt, Isaac Capone, Jack Fawdon, Riccardo Ruffo, Mauro Pasta|2020|Chem.Mater.|32|7653|doi:10.1021/acs.chemmater.0c01347
    Data Types:
    • Dataset
  • Related Article: Michele Fiore, Samuel Wheeler, Kevin Hurlbutt, Isaac Capone, Jack Fawdon, Riccardo Ruffo, Mauro Pasta|2020|Chem.Mater.|32|7653|doi:10.1021/acs.chemmater.0c01347
    Data Types:
    • Dataset
  • Related Article: Jacopo Perego, Silvia Bracco, Mattia Negroni, Charl X. Bezuidenhout, Giacomo Prando, Pietro Carretta, Angiolina Comotti, Piero Sozzani|2020|Nature Chemistry|12|845|doi:10.1038/s41557-020-0495-3
    Data Types:
    • Dataset
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