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Filling-in by joint interpolation of vector fields and gray levels
Abstract
A variational approach for filling-in regions of missing data in digital images is introduced. The approach is based on joint interpolation of the image gray levels and gradient/isophotes directions, smoothly extending in an automatic fashion the isophote lines into the holes of missing data. This interpolation is computed by solving the variational problem via its gradient descent flow, which leads to a set of coupled second order partial differential equations, one for the gray-levels and one for the gradient orientations. The process underlying this approach can be considered as an interpretation of the Gestaltist's principle of good continuation. No limitations are imposed on the topology of the holes, and all regions of missing data can be simultaneously processed, even if they are surrounded by completely different structures. Applications of this technique include the restoration of old photographs and removal of superimposed text like dates, subtitles, or publicity. Examples of these applications are given. We conclude the paper with a number of theoretical results on the proposed variational approach and its corresponding gradient descent flow.
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Citations
Cited by
Image Inpainting for Irregular Holes Using Partial Convolutions
Liu, G., Reda, F. A., Shih, K. J., Wang, T.-C., Tao, A., & Catanzaro, B. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01252-6_6 · Cited by 2,419
“Non-learning approaches to image inpainting rely on propagating appearance information from neighboring pixels to the target region using some mechanisms like distance field[3, 1, 30].”
BackgroundGlobally and locally consistent image completion
Iizuka, S., Simo-Serra, E., & Ishikawa, H. (2017) · ACM Transactions on Graphics · doi:10.1145/3072959.3073659 · Cited by 2,203
Pérez, P., Gangnet, M., & Blake, A. (2003) · ACM Transactions on Graphics · doi:10.1145/882262.882269 · Cited by 1,773
RePaint: Inpainting using Denoising Diffusion Probabilistic Models
Lugmayr, A., Danelljan, M., Romero, A., Yu, F., Timofte, R., & Van Gool, L. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01117 · Cited by 1,778
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Zhao, S., Cui, J., Sheng, Y., Dong, Y., Liang, X., Chang, E. I., & Xu, Y. (2021) · arXiv · doi:10.48550/arxiv.2103.10428 · Cited by 224
Metadata
- Authors
- Ballester, C., Bertalmio, M., Caselles, V., Sapiro, G., & Verdera, J.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2001
- Volume
- 10
- Issue
- 8
- Pages
- 1200-1211
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2100415658
- Cited by
- 962
- References
- 0
- FWCI
- 22.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ballester, C., Bertalmio, M., Caselles, V., Sapiro, G., & Verdera, J. (2001). Filling-in by joint interpolation of vector fields and gray levels. IEEE Transactions on Image Processing. https://doi.org/10.1109/83.935036
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