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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Veröffentlicht in:	IEEE transactions on image processing Jg. 25; H. 7; S. 3194 - 3207
Hauptverfasser:	Ding Liu, Zhaowen Wang, Bihan Wen, Jianchao Yang, Wei Han, Huang, Thomas S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	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-Zugang:	Volltext
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