Jointly Optimized Regressors for Image Super-resolution

Learning regressors from low‐resolution patches to high‐resolution patches has shown promising results for image super‐resolution. We observe that some regressors are better at dealing with certain cases, and others with different cases. In this paper, we jointly learn a collection of regressors, wh...

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Veröffentlicht in:	Computer graphics forum Jg. 34; H. 2; S. 95 - 104
Hauptverfasser:	Dai, D., Timofte, R., Van Gool, L.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Blackwell Publishing Ltd 01.05.2015
Schlagworte:	Analysis Approximation Categories and Subject Descriptors (according to ACM CCS) Computational efficiency Computer graphics Dealing Errors I.3.3 [Computer Graphics]: Image Generation-Display algorithms I.4.3 [Image Processing and Computer Vision]: Enhancement-Sharpening and deblurring Image processing systems Image resolution Labels Learning Optimization Regression analysis Studies Training
ISSN:	0167-7055, 1467-8659
Online-Zugang:	Volltext
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