Abstract
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.
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Keywords
- Regularization Term
- Regularization Approach
- Face Hallucination
- Reconstructed High Resolution Image
- Super Resolution Technique
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Rousseau, F. (2008). Brain Hallucination. In: Forsyth, D., Torr, P., Zisserman, A. (eds) Computer Vision – ECCV 2008. ECCV 2008. Lecture Notes in Computer Science, vol 5302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88682-2_38
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DOI: https://doi.org/10.1007/978-3-540-88682-2_38
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