Extraction of hidden information under sootiness on murals based on hyperspectral image enhancement

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%.