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Super-resolution Using Sub-space Models

  • David Capel
Chapter
Part of the Distinguished Dissertations book series (DISTDISS)

Abstract

In the previous chapter we demonstrated that generic MRF prior models can go a long way towards improving the performance of our super-resolution estimators. However, the generality of these priors is also their weakness, and in computing a superresolution MAP estimate, there is a trade-off to be made between reduced noise and excessive smoothness.

Keywords

Input Image Face Image Training Image Reconstruction Error Real Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • David Capel

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