L2-optimal image interpolation and its applications to medical imaging

Computer Science – Computer Vision and Pattern Recognition

Scientific paper

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Scientific paper

Digital medical images are always displayed scaled to fit particular view. Interpolation is responsible for this scaling, and if not done properly, can significantly degrade diagnostic image quality. However, theoretically-optimal interpolation algorithms may also be the most time-consuming and impractical. We propose a new approach, adapted to the needs of digital medical imaging, to combine high interpolation speed and superior L2-optimal image quality.

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