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  4. Vol 2, Issue 1, 2023

Research and Implementation of Inpainting Algorithms for Old Photos

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DOI: 10.23977/vcip.2023.020102 | Downloads: 9 | Views: 606

Author(s)

Shuili Zhang 1,2, Xue Tian 1, Luying Huang 1, Huaiyuan Sun 1

Affiliation(s)

1 College of Physics and Electronic Information, Yan'an University, Yan'an, Shaanxi, 716000, China
2 Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data, Yan'an University, Yan'an, Shaanxi, 716000, China

Corresponding Author

Shuili Zhang

ABSTRACT

In view of the scratches and red spots caused by the impact of time, environment and shooting equipment on the old photos, this paper uses MATLAB as image processing simulation software to carry out the research and implementation of image inpainting algorithm. By comparing and analyzing the repair effect and operational efficiency of the three basic models based on partial differential equations: BSCB model, TV model, and CDD model, the method of introducing weights into the TV model is selected to perform simple repair on color photos and black and white photos with scratches and red dots, and the repair results of old photos are presented through the MATLAB GUI interface. The experimental results show that the introduction of weight values in the TV model not only has a significant effect on solving the problem of unidirectional extension of the equal illuminance line in the TV model, but also has a good effect on repairing scratches and red dots in small-scale color and black and white photos.

KEYWORDS

Old photos, Repair, Scratches, Red dot, GUI

CITE THIS PAPER

Shuili Zhang, Xue Tian, Luying Huang, Huaiyuan Sun, Research and Implementation of Inpainting Algorithms for Old Photos. Visual Communications and Image Processing (2023) Vol. 2: 9-16. DOI: http://dx.doi.org/10.23977/vcip.2023.020102.

REFERENCES

[1] Bertalmio M, Sapiro G, Caselles Vetal. Image inpainting. Proceedings of International Conference on Conputer Graphics and Interactive Techniques, John Seely Brown, USA, 2000: 417-424.
[2] T. Chan, J. Shen. Mathematical Models for Local Non-texture lnpainting. SIAM, Apply Math, 2001 (62): 1019-1043.
[3] T. Chan, J. Shen. Non-texture Inpainting by Curvature Driven Diffusion (CDD). Journal of Visual Communication and Image Representation, 2001, 12 (4): 436-449.
[4] Suganuma M, Liu X, Okatani T. Attention-Based Adaptive Selection of Operations for Image Restoration in the Presence of Unknown Combined Distortions. 2019 IEE/CVF Conferenc-e on Computer Vision and Pattern Recognition (CVPR). Long Beach, USA: IEEE, 2019: 9031-9040.
[5] Wan Z Y, Zhang B, Chen D D, Zhang P, Chen D, Liao J and Wen F. Bringing old photos back to life. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, USA: IEEE, 2020: 2744−2754.
[6] Chen Y Y, Liu H.Y. Damaged Old Photos Inpainting Based on Generative Adversarial Networks. Computer and Modernization, 2021 (4): 42−47.
[7] Liu J X, Chen R and An S P.  Reference prior and generative prior linked distorted old photos restoration. Journal of Image and Graphics, 2022, 27 (05): 1657-1668.

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