Extraction of Hidden Information under Sootiness on Murals Based on Hyperspectral Image Enhancement
Source abstract
Abstract
Changes in the environment and human activities can cause serious deterioration of murals. Hyperspectral imaging technology can observe murals in the range of visible to near infrared light, providing a scientific and non-destructive way for mural digital preservation. An effective method to extract hidden information from the sootiness of murals in order to enhance the visual value of patterns in ancient murals using hyperspectral imaging is proposed in this paper. Firstly, Minimum Noise Fraction transform was applied to reduce sootiness features in the background of the mural. Secondly, analysis of spectral characteristics and image subtraction were used to achieve feature enhancement of the murals. Finally, density slicing was performed to extract the patterns under the sootiness. The results showed that the extraction of hidden information was achieved with an overall accuracy of 88.97%.
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Research context
OpenAlex topics: Cultural Heritage Materials Analysis · Remote-Sensing Image Classification · Color Science and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, No.15 Yongyuan Road, Daxing District, Beijing 102616, China
Beijing Key Laboratory for Architectural Heritage Fine Reconstruction & Health Monitoring, No.15 Yongyuan Road, Daxing District, Beijing 102616, China
College of Geoscience and Surveying Engineering, China University of Mining and Technology, No.11, Xueyuan Road, Haidian District, Beijing 100083, China
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