A comprehensive dataset for digital restoration of Dunhuang murals

The MuralDH dataset is an invaluable digital resource developed for the conservation and restoration of Dunhuang murals, which are critical components of global cultural heritage facing threats from degradation. This dataset comprises over 5000 high-resolution images tailored to 512x512 pixels, emphasizing the preservation of mural integrity and detail. It includes 1000 images with pixel-level damage annotations for segmentation research and 500 images specially processed for super-resolution studies, catering to a wide range of digital restoration needs. While the primary focus of this work is the dataset itself, we also introduce a supportive digital restoration framework. This framework, which encompasses damage segmentation, inpainting, and super-resolution techniques, serves as a secondary validation of MuralDH’s utility and versatility. Through MuralDH, technology revives ancient art, embodying the essence of interdisciplinary innovation. By facilitating advanced research in compu..., , , # A comprehensive dataset for digital restoration of Dunhuang murals

[https://doi.org/10.5061/dryad.bnzs7h4jd](https://doi.org/10.5061/dryad.bnzs7h4jd)

The MuralDH dataset is a comprehensive collection of high-quality images for the digital restoration of Dunhuang murals. It includes over 5000 pre-processed images, curated to support research in digital art restoration, computer vision, and cultural heritage preservation. This dataset is divided into segments including damaged mural segmentation, high-resolution mural images, and images processed for super-resolution studies. The collection, designed to assist in the development and testing of digital restoration algorithms, aims to bridge traditional art with modern technology, ensuring the longevity and accessibility of these invaluable cultural treasures.

## Description of the data and file structure

The dataset is structured as follows:

* **Damaged Mural Segmentation Dataset:** 1000 images annotated for specific types of damage...