Revealing Disappearance Patterns in Murals Heavily Contaminated by Soot Based on Hyperspectral Imaging.
Over time, many murals have become heavily contaminated with soot, obscuring patterns and hindering the recognition of these significant cultural relics. This study utilises the spectral discrimination and subsurface detection capabilities of hyperspectral imaging to nondestructively reveal pattern...
| Publicado en: | Archaeometry Vol. 68; no. 3; pp. 527 - 540 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
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Wiley-Blackwell
Jun2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=193599604&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 193599604 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 0003813X D7X jtl: Archaeometry issn: 0003813X maglogo: Y pubinfo: dt: Jun2026 vid: 68 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 193599604 10.1111/arcm.70076 ppf: 527 ppct: 13 formats: tig: atl: Revealing Disappearance Patterns in Murals Heavily Contaminated by Soot Based on Hyperspectral Imaging. aug: au: Sun, Pengyu Hou, Miaole Lyu, Shuqiang Cui, Wenyi Wang, Wanfu Sun, Yutong affil: Beijing University of Civil Engineering and Architecture, Beijing, China Beijing Key Laboratory for Architectural Heritage Fine Reconstruction & Health Monitoring, Beijing, China The Dunhuang Academy, Dunhuang, China China Academy of Cultural Heritage, Beijing, China su: Hyperspectral imaging systems Art conservation & restoration Image enhancement (Imaging systems) Pollution Pattern perception Independent component analysis Cultural property Archaeology sug: subj: Hyperspectral imaging systems Art conservation & restoration Image enhancement (Imaging systems) Pollution Pattern perception Independent component analysis Cultural property Archaeology keyword: EMP‐PCA hidden information hyperspectral imaging sooty murals weight map ab: Over time, many murals have become heavily contaminated with soot, obscuring patterns and hindering the recognition of these significant cultural relics. This study utilises the spectral discrimination and subsurface detection capabilities of hyperspectral imaging to nondestructively reveal pattern information concealed by soot. After preprocessing the hyperspectral data, independent component analysis (ICA) is used to preliminarily separate soot from the underlying patterns. Several independent components containing the most distinct pattern information are selected for a two‐part enhancement strategy. The first part introduces a novel feature extraction method, EMP‐PCA, to highlight and extract the patterns, followed by contrast stretching to enhance the pattern–background distinction. The second part uses an inverse ICA transformation on selected components to synthesise a true colour image, which is then enhanced using a weight map–based method. Finally, the results from both parts are combined using Laplacian fusion, comprehensively revealing the patterns hidden beneath the heavy soot. The results demonstrate the method's effectiveness and provide valuable information for the archaeological study and conservation of cultural heritage. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
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