Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30572
Title: An efficient example-based approach for image super-resolution
Authors: Li, X
Lam, KM 
Qiu, G
Shen, L
Wang, S
Keywords: Class-specific pred
Example-based Super-resolution
Human face magnification
Issue Date: 2008
Publisher: IEEE
Source: 2008 International Conference on Neural Networks and Signal Processing, 7-11 June 2008, Nanjing, p. 575-580 How to cite?
Abstract: A novel algorithm for image super-resolution with class-specific predictors is proposed in this paper. In our algorithm, the training example images are classified into several classes, and each patch of a low-resolution image is classified into one of these classes. Each class has its high-frequency information inferred using a class-specific predictor, which is trained via the training samples from the same class. In this paper, two different types of training sets are employed to investigate the impact of the training database to be used. Experimental results have shown the superior performance of our method.
Description: Best Paper Award
URI: http://hdl.handle.net/10397/30572
ISBN: 978-1-4244-2310-1
978-1-4244-2311-8 (E-ISBN)
DOI: 10.1109/ICNNSP.2008.4590416
Appears in Collections:Conference Paper

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