《Example-based regularization deployed to super-resolution reconstruction of a single image》.pdf

The Computer Journal Advance Access published April 20, 2007 # The Author 2007. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org doi:10.1093/comjnl/bxm008 Example-Based Regularization Deployed to Super-Resolution Reconstruction of a Single Image MICHAEL ELAD * AND DMITRY DATSENKO Department of Computer Science, The Technion—Israel Institute of Technology, Haifa 32000, Israel *Corresponding author: elad@cs.technion.ac.il In super-resolution (SR) reconstruction of images, regularization becomes crucial when insufficient number of measured low-resolution images is supplied. Beyond making the problem algebraically well posed, a properly chosen regularization can direct the solution toward a better quality outcome. Even the extreme case—a SR reconstruction from a single measured image—can be made successful with a well-chosen regularization. Much of the progress made in the past two decades on inverse problems in image processing can be attributed to the advances in forming or choosing the way to practice the regularization. A Bayesian point of view interpret this as a way of including the prior distribution of images, which sheds some light on the complications involved. This paper reviews an emergin