Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Example-based single document image super-resolution: a global MAP approach with outlier rejection
Multidimensional Systems and Signal Processing
Face Hallucination: Theory and Practice
International Journal of Computer Vision
MRI superresolution using self-similarity and image priors
Journal of Biomedical Imaging
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In this paper, we investigate brain hallucination, or generating a high resolution brain image from an input low-resolution image, with the help of another high resolution brain image. Contrary to interpolation techniques, the reconstruction process is based on a physical model of image acquisition. Our contribution is a new regularization approach that uses an example-based framework integrating non-local similarity constraints to handle in a better way repetitive structures and texture. The effectiveness of our approach is demonstrated by experiments on realistic Magnetic Resonance brain images generating automatically high-quality hallucinated brain images from low-resolution input.