Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

Single image super-resolution (SR) is an ill-posed problem, which tries to recover a high-resolution image from its low-resolution observation. To regularize the solution of the problem, previous methods have focused on designing good priors for natural images, such as sparse representation, or dire...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 25; no. 7; pp. 3194 - 3207
Main Authors:	Ding Liu, Zhaowen Wang, Bihan Wen, Jianchao Yang, Wei Han, Huang, Thomas S.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.07.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Coding deep neural networks Degradation Dictionaries Image coding Image resolution image super-resolution Learning Machine learning Networks Neural networks Scaling factors sparse coding Training sparse coding deep neural networks Image super-resolution
ISSN:	1057-7149, 1941-0042
Online Access:	Get full text
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