[1] Yang Z R. The experiment of uncovering ancient frescoes with earth method was successful[J]. Cultural Relics, 15(1958).

[3] Wang J R. Digital acquisition technology and application of high-precision images of Tang tomb murals[J]. Relics and Museolgy, 66-70(2011).

[4] Karianakis N, Maragos P. An integrated system for digital restoration of prehistoric Theran wall paintings[C](2013).

[5] Jaidilert S, Farooque G. Crack detection and images inpainting method for Thai mural painting images[C], 143-148(2018).

[6] Criminisi A, Perez P, Toyama K. Region filling and object removal by exemplar-based image inpainting[J]. IEEE Transactions on Image Processing, 13, 1200-1212(2004).

[7] Purkait P, Ghorai M, Samanta S et al. A patch-based constrained inpainting for damaged mural images[M]. Mallik A, Chaudhury S, Chandru V, et al. Digital Hampi: preserving Indian cultural heritage, 205-223(2017).

[8] Chen Y, Tao M F, Ai Y P et al. Algorithm for Dunhuang mural inpainting based on Gabor transform and group sparse representation[J]. Laser & Optoelectronics Progress, 57, 221015(2020).

[9] Chen Y, Chen J, Ai Y P et al. Dunhuang mural inpainting algorithm based on sequential similarity detection and cuckoo optimization[J]. Laser & Optoelectronics Progress, 57, 201020(2020).

[10] Pathak D, Krähenbühl P, Donahue J et al. Context encoders: feature learning by inpainting[C], 2536-2544(2016).

[11] Iizuka S, Simo-Serra E, Ishikawa H. Globally and locally consistent image completion[J]. ACM Transactions on Graphics, 36, 107(2017).

[12] Paunwala C N. Image inpainting evolution: a survey[M]. Encyclopedia of image processing, 319-333(2018).

[13] Laube P, Grunwald M, Franz M O et al. Image inpainting for high-resolution textures using CNN texture synthesis[EB/OL]. https://arxiv.org/abs/1712.03111

[14] Peng G Z, Chen W J. Fringe pattern inpainting based on convolutional neural network denoising regularization[J]. Acta Optica Sinica, 40, 1810002(2020).

[15] Sabini M, Rusak G. Painting outside the box: image outpainting with GANs[EB/OL]. https://arxiv.org/abs/1808.08483

[16] Goodfellow I J, Pouget-Abadie J, Mirza M et al. Generative adversarial networks[EB/OL]. https://arxiv.org/abs/1406.2661

[17] Chen J Z, Wang J, Gong X. Face image inpainting using cascaded generative adversarial networks[J]. Journal of University of Electronic Science and Technology of China, 48, 910-917(2019).

[18] Vaswani A, Shazeer N, Parmar N et al. Attention is all you need[EB/OL]. https://arxiv.org/abs/1706.03762

[19] Risser E, Wilmot P, Barnes C. Stable and controllable neural texture synthesis and style transfer using histogram losses[EB/OL]. https://arxiv.org/abs/1701.08893

[20] Gulrajani I, Ahmed F, Arjovsky M et al. Improved training of Wasserstein GANs[EB/OL]. https://arxiv.org/abs/1704.00028

[21] Zhu X C, Tang G J. Overview of visual quality assessment methods[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 38, 1-11(2018).

[22] Wen Y H, Yang K, Li B. Performance test for image quality assessment[J]. Chinese Space Science and Technology, 30, 72-77(2010).

[23] Li C Y, Wang H Q, Wu M et al. Automatic recognition and virtual restoration of mud spot disease of Tang dynasty tomb murals image[J]. Computer Engineering and Applications, 52, 233-236(2016).

[24] Shen J N, Wang H Q, Wu M et al. Tang dynasty tomb murals inpainting algorithm of MCA decomposition[J]. Journal of Frontiers of Computer Science and Technology, 11, 1826-1836(2017).

[25] Ma D A, Tang P, Zhao L J et al. Review of data augmentation for image in deep learning[J]. Journal of Image and Graphics, 26, 487-502(2021).

[26] Park D Y, Lee K H. Arbitrary style transfer with style-attentional networks[C], 5880-5888(2019).