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Example-based super-resolution

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3 Author(s)
Freeman, W.T. ; Artificial Intelligence Lab., MIT, Cambridge, MA, USA ; Jones, T.R. ; Pasztor, E.C.

We call methods for achieving high-resolution enlargements of pixel-based images super-resolution algorithms. Many applications in graphics or image processing could benefit from such resolution independence, including image-based rendering (IBR), texture mapping, enlarging consumer photographs, and converting NTSC video content to high-definition television. We built on another training-based super-resolution algorithm and developed a faster and simpler algorithm for one-pass super-resolution. Our algorithm requires only a nearest-neighbor search in the training set for a vector derived from each patch of local image data. This one-pass super-resolution algorithm is a step toward achieving resolution independence in image-based representations. We don't expect perfect resolution independence-even the polygon representation doesn't have that-but increasing the resolution independence of pixel-based representations is an important task for IBR

Published in:

Computer Graphics and Applications, IEEE  (Volume:22 ,  Issue: 2 )

Date of Publication:

Mar/Apr 2002

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