Article: Digital reconstruction method of intangible cultural heritage painting integrating MSI and improved U-Net Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.30 pp.49 - 72 Abstract: Intangible cultural heritage paintings often suffer from fading, structural damage, and detail loss due to environmental and material aging, making high-fidelity digital reconstruction essential for cultural preservation. To address the limitations of red-green-blue imaging (RGB) and insufficient spectral-spatial modelling, this study proposes context-aware multi-spectral imaging network (CA-MSI-Net), a reconstruction method integrating multi-spectral imaging (MSI) with an improved U-Net architecture. Spatial and channel transformer modules are embedded to enhance long-range spatial dependencies and cross-band spectral interactions, while contextual modelling and multi-scale attention mechanisms strengthen texture perception and boundary restoration. Experiments on multispectral datasets demonstrate that CA-MSI-Net achieves superior reconstruction accuracy, with mean intersection over union (mIoU), dice similarity coefficient (DSC), and F1 score reaching 81.3%, 92.1%, and 0.94, respectively, outperforming UCTransNet and dynamic optimisation vision network (DovNet). The method shows robust performance across painting styles, lighting conditions, and spectral configurations. Inderscience Publishers - linking academia, business and industry through research

Title: Digital reconstruction method of intangible cultural heritage painting integrating MSI and improved U-Net

Authors: Bin Chen

Addresses: School of Arts, Minnan Normal University, Zhangzhou, 363000, China

Abstract: Intangible cultural heritage paintings often suffer from fading, structural damage, and detail loss due to environmental and material aging, making high-fidelity digital reconstruction essential for cultural preservation. To address the limitations of red-green-blue imaging (RGB) and insufficient spectral-spatial modelling, this study proposes context-aware multi-spectral imaging network (CA-MSI-Net), a reconstruction method integrating multi-spectral imaging (MSI) with an improved U-Net architecture. Spatial and channel transformer modules are embedded to enhance long-range spatial dependencies and cross-band spectral interactions, while contextual modelling and multi-scale attention mechanisms strengthen texture perception and boundary restoration. Experiments on multispectral datasets demonstrate that CA-MSI-Net achieves superior reconstruction accuracy, with mean intersection over union (mIoU), dice similarity coefficient (DSC), and F1 score reaching 81.3%, 92.1%, and 0.94, respectively, outperforming UCTransNet and dynamic optimisation vision network (DovNet). The method shows robust performance across painting styles, lighting conditions, and spectral configurations.

Keywords: intangible cultural heritage painting; digital reconstruction; multi-scale attention mechanism; multi-spectral imaging; U-Net.

DOI: 10.1504/IJICT.2026.152658

International Journal of Information and Communication Technology, 2026 Vol.27 No.30, pp.49 - 72

Received: 13 Oct 2025
Accepted: 18 Dec 2025
Published online: 01 Apr 2026 *

Title: Digital reconstruction method of intangible cultural heritage painting integrating MSI and improved U-Net

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