Virtual restoration of stains on ancient paintings with maximum noise fraction transformation based on the hyperspectral imaging.

Abstract Ancient paintings, as one of the most important forms of artistic expression of Chinese traditional culture, are the most valuable and non-renewable treasure of human civilization. However, unfortunate situations occur, causing stains on paintings. Stains disfigure their artistry and values...

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Publicado en:Journal of Cultural Heritage Vol. 34; pp. 136 - 145
Autores principales: Hou, Miaole, Zhou, Pingping, Lv, Shuqiang, Hu, Yungang, Zhao, Xuesheng, Wu, Wangting, He, Haiping, Li, Songnian, Tan, Li
Formato: Artículo
Publicado: Elsevier B.V. Nov2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2018
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      pub: Elsevier B.V.
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        10.1016/j.culher.2018.04.004
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        atl: Virtual restoration of stains on ancient paintings with maximum noise fraction transformation based on the hyperspectral imaging.
      aug:
        au:
          Hou, Miaole
          Zhou, Pingping
          Lv, Shuqiang
          Hu, Yungang
          Zhao, Xuesheng
          Wu, Wangting
          He, Haiping
          Li, Songnian
          Tan, Li
        affil:
          Beijing University of Civil Engineering and Architecture, no. 1, Zhanlanguan Road D, Xicheng District, 100044 Beijing, PR China
          China University of Mining and Technology, no. 11, Xueyuan Road D, Haidian District, Beijing, PR China
          Capital Museum, no. 1, Baiyun Road D, Xicheng District, 100045 Beijing, PR China
          Ryerson university, Toronto, Canada
      su:
        Qing dynasty, China, 1644-1912
        Hyperspectral imaging systems
        Principal components analysis
        Civilization
        Imaging systems
      sug:
        subj:
          Qing dynasty, China, 1644-1912
          Hyperspectral imaging systems
          Principal components analysis
          Civilization
          Imaging systems
      keyword:
        Ancient paintings
        Hyperspectral imaging
        Maximum noise fraction transformation
        Stains
        Virtual restoration
      ab: Abstract Ancient paintings, as one of the most important forms of artistic expression of Chinese traditional culture, are the most valuable and non-renewable treasure of human civilization. However, unfortunate situations occur, causing stains on paintings. Stains disfigure their artistry and values, and it is desirable to remove them. Traditional removal methods using physical means or chemicals may damage the original paintings. Recent virtual restoration effort may cause inconsistent content when applied to larger regions. This paper proposes a new virtual restoration method of stains based on the maximum noise fraction (MNF) transformation with the hyperspectral imaging. The method has two steps. Firstly, it carries out the forward MNF transformation to concentrate the main features of ancient paintings into the several top principal components. Secondly, it determines the principal component that contains the large spectral information of stains, and applies the inverse MNF transformation to several top components except for the chosen components to reduce the stain effect on the image and restore the original spectral information and color as much as possible. This paper selects a paper painting of the Qing Dynasty as the experiment data, and the results show that the method has the effect of diluting or eliminating image spots, and can restore the style of ancient paintings to a large extent without causing a large loss of data information.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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