Evidence map›Paper›PMID 39517424›Full record

ArticleMaterials (Basel, Switzerland)2024

A Study on Pigment Composition of Buddhist Cave Paintings Based on Hyperspectral Technology.

Xiang Shi, Xiaogang Lin, Yu Lei, Jinyu Wu, Xiao Lv, Yong Zhou

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xiang ShiKey Laboratory of Optoelectronic Technology and Systems of Ministry of Education of China, Chongqing University, Chongqing 400044, China.
Xiaogang LinKey Laboratory of Optoelectronic Technology and Systems of Ministry of Education of China, Chongqing University, Chongqing 400044, China.ORCID 0000-0001-9255-0672
Yu LeiAcademy of Dazu Rock Carvings, Chongqing 402360, China.
Jinyu WuKey Laboratory of Optoelectronic Technology and Systems of Ministry of Education of China, Chongqing University, Chongqing 400044, China.
Xiao LvKey Laboratory of Optoelectronic Technology and Systems of Ministry of Education of China, Chongqing University, Chongqing 400044, China.
Yong ZhouKey Laboratory of Optoelectronic Technology and Systems of Ministry of Education of China, Chongqing University, Chongqing 400044, China.ORCID 0000-0002-2925-3912

Funding

Frontier Research Project of Chongqing No. CSTB2023NSCQ-MSX0231National Key R&D Program of China No. 2020YFC1522900
6 · The paper itself

Abstract

The value of the Buddhist cave lies not only in the Buddha statues but also in the surface painting. Hyperspectral imaging technology, as an emerging and effective method for component identification, offers a non-contact and non-destructive approach to the preservation and restoration of oil paintings. This study employed hyperspectral cameras to capture common pigments on the surfaces of Buddhist caves. Then, the results were processed and used as a database to identify the paintings. Additionally, a series of experiments were conducted to examine the impact of binder, substrate types, and pigment sizes on the reflectance spectrum of the paints. The Spectral Angle Matching (SAM) algorithm was then used to analyze the Yuanjue Cave and Qiqushan Stone Carvings of the Tang Dynasty in China. The findings revealed that the position of absorption peaks in the reflectance spectra is not significantly influenced by the substrate but is affected by the binder. Moreover, the absorption depth varies regularly with particle size. Furthermore, the spectral matching results demonstrate that components can be accurately identified even for similar colors. Based on the pigment distribution, the study also inferred specific details of ancient paintings, including the painting steps and hidden information in the manuscript layout. These findings hold significant implications for the restoration of representative surface paintings of the Tang Dynasty Buddhist cave, providing a reference for the selection of restoration materials and methods.

Indexed as

buddhist cave paintingshigh-spectrum imagingnon-destructive analysisSAM

Identifiers

PMID39517424
PMCPMC11547554

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