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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Bibliographic Details
Published in:	Computer graphics forum Vol. 34; no. 2; pp. 95 - 104
Main Authors:	Dai, D., Timofte, R., Van Gool, L.
Format:	Journal Article
Language:	English
Published:	Oxford Blackwell Publishing Ltd 01.05.2015
Subjects:	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 Access:	Get full text
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