Standard Multispectral Image Database for Paint Materials Used in the Dunhuang Murals
CHAI Bo-long1,2, SU Bo-min1,2*, ZHANG Wen-yuan1,2, WANG Xiao-wei1,2, LI Ling-zhi1,2
1. National Research Center for Conservation of Ancient Wall Paints and Earthen Ruins, Dunhuang 736200, China
2. Conservation Institution of Dunhuang Academy, Dunhuang 736200, China
Abstract:Multispectral imaging techniques are based on the facts that each substance has a characteristic absorbance and reflectance spectrum. Besides, it takes into consideration the fact that the corresponding color biases in different monochromatic spectral ranges may be enhanced by converting the monochromatic greyscale image into a false-color image. Thus, multispectral imaging may be applied to the investigation of painting materials. It is, however, necessary to first establish a multispectral image database for archeological painting materials. Such a database would enable multispectral imaging to be used to conduct preliminary surveys on undecipherable sections of murals, pigments of similar hue, and organic materials that cannot be observed under visible light. The preliminary survey results may then be used as a basis for more detailed studies conducted using high-precision instruments. In this study, a standard pigment color chart was created using the 29 painting materials that are known to have been used in the Dunhuang murals. Reflectance and fluorescence imaging of the pigments was performed in various spectral ranges between 250 and 1 300 nm, using a standardized multispectral imaging procedure under optimized multispectral imaging conditions. The resulting data were then post-processed and combined with infrared (IR) and ultraviolet (UV) reflectance false-color images for use in the preliminary construction of a standard multispectral image database for the painting materials used in the Dunhuang murals. Multispectral imaging was then performed on actual murals to simultaneously collect visible, IR, and UV reflectance false-color images that were then compared with the standard image database. The multispectral imaging results were analyzed via comparisons with data obtained using portable microscopy, portable x-ray fluorescence spectrometry, and near-infrared spectroscopy. The results show that the establishment of a standard multispectral image database for mural painting materials can be applied as a new nondestructive analytical method. This method can be used in the preliminary verification of painting materials used in the Dunhuang murals, to identify the properties of the painting materials, and to obtain information such as pigment distributions. The establishment of this database will also increase the reliability and effectiveness of preliminary studies on the type and scope of commonly observed painting materials. Thus, it is expected to be useful in pigment studies.
基金资助: (973) National Research Topic (2012CB720900), Gansu Province Cultural Heritage Protection Research Topic (2012061)
通讯作者:
苏伯民
E-mail: suboming@hotmail.com
作者简介: CHAI Bo-long, (1978—), associate researcher in the Conservation Institute of Dunhuang Academy, is primarily responsible for multispectral photography in conservation studies on the Dunhuang murals e-mail:
107787314@qq.com
引用本文:
柴勃隆,苏伯民,张文元,王小伟,李凌志. 敦煌壁画绘画材料多光谱图像标准数据库的建立和应用[J]. 光谱学与光谱分析, 2017, 37(10): 3289-3306.
CHAI Bo-long, SU Bo-min, ZHANG Wen-yuan, WANG Xiao-wei, LI Ling-zhi. Standard Multispectral Image Database for Paint Materials Used in the Dunhuang Murals. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(10): 3289-3306.
[1] Pelagotti A, Del Mastio A, De Rosa A, et al. IEEE Signal Processing Magazine, 2008, 25(4): 27.
[2] Zhao L, Li Y, Fan Y, et al. Dunhuang Research, 2010, (6): 69.
[3] Cosentino A, Gil M, Ribeiro M, et al. Conservar Património, 2014, 20(23-33).
[4] Delaney J K, Zeibel J G, Thoury M, et al. Applied Spectroscopy, 2010, 64(6): 584.
[5] Dooley K A, Lomax S, Zeibel J G, et al. Analyst, 2013, 138(17): 4838.
[6] Ricciardi P, Delaney J K, Facini M, et al. Angewandte Chemie International Edition, 2012, 51(23): 5607.
[7] Chai B, Fan Y, Su B, et al. Dunhuang Research, 2011, 6:74.
[8] Teke M, Ba eski E, Ok A , et al. Multi-Spectral False Color Shadow Detection. Photogrammetric Image Analysis,Springer, 2011. 109.