NEWS ARTICLE
学术动态：Hyperspectral Imaging for the Colorimetric Characterization of Purple Manuscripts: Accuracy, Biases, and Diagnosti.
论文标题：Hyperspectral Imaging for the Colorimetric Characterization of Purple Manuscripts: Accuracy, Biases, and Diagnostic Potential
发布日期：2026-05-26
作者：Cristina Fornacelli, Costanza Cucci, Andrea Casini, Maurizio Aceto, Marcello Picollo
DOI：10.3390/s26113358
论文摘要：Color measurement and monitoring of chromatic changes over time play a key role in the study and conservation of historical materials. In this context, hyper-spectral imaging (HSI) offers spatially resolved spectral information that can be converted into colorimetric data, although its quantitative reliability under in situ conditions remains challenging. This study evaluates the colorimetric performance of a HSI system (Specim IQ) through comparison with a reference spectrocolorimeter (Konica-Minolta CM-700d), combining laboratory measurements on certified standards and in situ analyses on purple-dyed manuscripts. Colorimetric coordinates (CIELAB) and color differences (ΔE00) were used to assess accuracy, precision, and systematic deviations. Under controlled conditions, HSI showed good agreement with reference measurements, although systematic biases were observed. In situ applications revealed reduced accuracy (average ΔE00 ≈ 4.3) due to material heterogeneity and acquisition constraints. Despite these limitations, HSI preserved consistent relative chromatic relationships, enabling meaningful comparative analysis. Spatially resolved mapping of colorimetric parameters proved effective for visualizing chromatic variability, dye distribution, and degradation patterns. These results demonstrate that, while not fully reliable for absolute colorimetric assessment in situ, HSI represents a powerful tool for non-invasive, spatially resolved color analysis of complex historical materials.
元数据：Crossref 收录的 MDPI Sensors 论文。 DOI: 10.3390/s26113358. Vol. 26, Issue 11. Authors: Cristina Fornacelli, Costanza Cucci, Andrea Casini, Maurizio Aceto, Marcello Picollo.
开放许可：https://creativecommons.org/licenses/by/4.0/
原文链接：https://doi.org/10.3390/s26113358
PDF 链接：https://www.mdpi.com/1424-8220/26/11/3358/pdf