Optimized Method for Mapping Inorganic Pigments by Means of Multispectral Imaging Combined with Hyperspectral Spectroscopy for the Study of Vincenzo Pasqualoni’s Wall Painting at the Basilica of S. Nicola in Carcere in Rome
Optimized Method for Mapping Inorganic Pigments by Means of Multispectral Imaging Combined with Hyperspectral Spectroscopy for the Study of Vincenzo Pasqualoni’s Wall Painting at the Basilica of S. Nicola in Carcere in Rome
复制标题
多光谱成像与高光谱光谱相结合的无机颜料测绘优化方法，用于研究罗马卡塞尔圣尼古拉大教堂的文森佐·帕斯夸洛尼壁画
作者：
L. Pronti;G. Capobianco;M. Vendittelli;A. C. Felici;S. Serranti;G. Bonifazi
多光谱成像是研究绘画的初步筛选技术。虽然它允许通过它们的光谱行为来识别几种矿物颜料，但它被认为在高光谱成像方面表现不佳，因为选择了有限数量的波长。在这项工作中，我们提出了一个优化的方法来映射的分布的矿物颜料所使用的帕斯夸洛尼为他的壁画放置在巴西利卡的S。Nicola在罗马的Carcere，结合UV/维斯/NIR反射光谱和多光谱成像。第一种方法（UV/维斯/NIR反射光谱）使我们能够以高光谱分辨率表征颜料层;第二种方法（UV/维斯/NIR多光谱成像）允许通过利用有限数量的波长来评估颜料分布。结合从两个装置获得的结果，可以获得具有高精度水平的颜料识别的图像层的分布图。该方法涉及联合使用逐点高光谱光谱和主成分分析（PCA）来识别调色板中的颜料，并使用通过多光谱成像系统获得的少量波长来评估区分所有识别颜料的可能性。最后，通过主成分分析假彩色图像显示了多光谱图像中识别的不同颜料（在这种情况下：红赭石，黄赭石，雌黄，钴蓝基颜料，群青和Chrome绿色）的分布和光谱差异。
Multispectral imaging is a preliminary screening technique for the study of paintings. Although it permits the identification of several mineral pigments by their spectral behavior, it is considered less performing concerning hyperspectral imaging, since a limited number of wavelengths are selected. In this work, we propose an optimized method to map the distribution of the mineral pigments used by Vincenzo Pasqualoni for his wall painting placed at the Basilica of S. Nicola in Carcere in Rome, combining UV/VIS/NIR reflectance spectroscopy and multispectral imaging. The first method (UV/VIS/NIR reflectance spectroscopy) allowed us to characterize pigment layers with a high spectral resolution; the second method (UV/VIS/NIR multispectral imaging) permitted the evaluation of the pigment distribution by utilizing a restricted number of wavelengths. Combining the results obtained from both devices was possible to obtain a distribution map of a pictorial layer with a high accuracy level of pigment recognition. The method involved the joint use of point-by-point hyperspectral spectroscopy and Principal Component Analysis (PCA) to identify the pigments in the color palette and evaluate the possibility to discriminate all the pigments recognized, using a minor number of wavelengths acquired through the multispectral imaging system. Finally, the distribution and the spectral difference of the different pigments recognized in the multispectral images, (in this case: red ochre, yellow ochre, orpiment, cobalt blue-based pigments, ultramarine and chrome green) were shown through PCA false-color images.