Blind Super-Resolution Using a Learning-Based Approach

Isabelle B?gin; Frank P. Ferrie

doi:10.1109/ICPR.2004.1334046

Pattern Recognition, International Conference on

Blind Super-Resolution Using a Learning-Based Approach

Year: 2004, Pages: 85-89

DOI Bookmark: 10.1109/ICPR.2004.1334046

Authors

Isabelle B?gin, McGill University, Canada
Frank P. Ferrie, McGill University, Canada

Abstract

The super-resolution of a single image of unknown point-spread-function (PSF) is addressed by extending a learning framework using blind deconvolution with an uncertainty around the resulting PSF. Results indicate success in refining the estimate of the PSF as well as to restoring the image. A novel disparity measure is also proposed to quantify the results.

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Blind Super-Resolution Using a Learning-Based Approach

Authors

Abstract

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