Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1169-1172, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1169-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1169-1172, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1169-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

THE COMPARISON BETWEEN NMF AND ICA IN PIGMENT MIXTURE IDENTIFICATION OF ANCIENT CHINESE PAINTINGS

Y. Liu1, S. Lyu1,2,3, M. Hou1,2,3, and Q. Yin2 Y. Liu et al.
  • 1School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, No.15Yongyuan Road, Daxing District, Beijing, 102616, China
  • 2Beijing Key Laboratory For Architectural Heritage Fine Reconstruction & Health Monitoring, No.15Yongyuan Road, Daxing District, Beijing, 102616, China
  • 3Engineering Research Center of Representative Building and Architectural Heritage Database, Ministry of Education, No.15Yongyuan Road, Daxing District, Beijing, 102616, China

Keywords: Hyperspectral Imaging, Painting Relics, Blind Source Separation Algorithm, Non-negative Matrix Factorization, Independent Component Analysis

Abstract. Since the colour in painting cultural relics observed by our naked eyes or hyperspectral cameras is usually a mixture of several kinds of pigments, the mixed pigments analysis will be an important subject in the field of ancient painting conservation and restoration. This paper aims to find a more effective method to confirm the types of every pure pigment from mixture on the surface of paintings. Firstly, we adopted two kinds of blind source separation algorithms, which are independent component analysis and non-negative matrix factorization, to extract the pure pigment component from mixed spectrum respectively. Moreover, we matched the separated pure spectrum with the pigments spectra library built by our team to determine the pigment type. Furthermore, three kinds of data including simulation data, mixed pigments spectral data measured in laboratory, and the spectral data of an ancient painting were chosen to evaluate the performance of the different algorithms. And the accuracy was compared between the two algorithms. Finally, the experimental results show that non-negative matrix factorization method is more suitable for endmember extraction in the field of ancient painting conservation and restoration.