Single Image Super-Resolution: From Sparse Coding to Deep Learning
Ding Liu⁎; Thomas S. Huang† ⁎Beckman Institute for Advanced Science and Technology, Urbana, IL, United States†Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States
Abstract
Recently, deep learning has been successfully applied in numerous areas of computer vision, including low-level image restoration problems. For single image super-resolution (SR), which is an ill-posed problem that tries to recover a high-resolution image from its low-resolution observation, a number of models based on deep neural networks have been proposed and obtained superior performance that overshadows all previously ...
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