Image Interpolation using Infinite Laplacian Solution

This repository implements an innovative approach to image interpolation based on the concept of minimizing the sup norm of the gradient, inspired by the works of Caselles et al. and Jensen.

Features

• Infinite Laplacian Solution: Utilizes a semi-implicit numerical scheme for image reconstruction.
• Lipschitz Extensions: Ensures uniqueness and quality of interpolations.
• Python Implementation: Efficient algorithms for practical image processing tasks.

Contributing

Contributions are welcome! Feel free to open issues or pull requests for features, bug fixes, or documentation improvements.

References

• Caselles, V., Morel, J.-M., Sbert, C. "An axiomatic approach to image interpolation." IEEE Transactions on Image Processing, 1998.
• Jensen, R. "Uniqueness of Lipschitz extensions: Minimizing the sup norm of the gradient." Archive for Rational Mechanics and Analysis, 1993.

License

This project is licensed under the MIT License - see the LICENSE file for details.