NDLI: Single-image super-resolution via local learning

Content Provider	Springer Nature Link
Author	Tang, Yi Yan, Pingkun Yuan, Yuan Li, Xuelong
Copyright Year	2011
Abstract	Nearest neighbor-based algorithms are popular in example-based super-resolution from a single image. The core idea behind such algorithms is that similar images are close in the sense of distance measurement. However, it is well known in the field of machine learning and statistical learning theory that the generalization of the nearest neighbor-based estimation is poor, when complex or high dimensional data are considered. To improve the power of the nearest neighbor-based algorithms in single-image based super-resolution, a local learning method is proposed in this paper. Similar to the nearest neighbor-based algorithms, a local training set is generated according to the similarity between the training samples and a given test sample. For super-resolving the given test sample, a local regression function is learned on the local training set. The generalization of nearest neighbor-based algorithms can be enhanced by the process of local regression. Based on such an idea, we propose a novel local-learning-based algorithm, where kernel ridge regression algorithm is used in local regression for its well generalization. Some experimental results verify the effectiveness and efficiency of the local learning algorithm in single-image based super-resolution.
Starting Page	15
Ending Page	23
Page Count	9
File Format	PDF
ISSN	18688071
Journal	International Journal of Machine Learning and Cybernetics
Volume Number	2
Issue Number	1
e-ISSN	1868808X
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-02-12
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Super-resolution Local learning Generalization Reproducing kernel Kernel ridge regression Similarity Systems Biology Computational Intelligence Control Robotics Mechatronics Pattern Recognition Statistical Physics, Dynamical Systems and Complexity Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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