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Non-parametric single image super resolution

Authors: Yunsang Han; Tae-Byeong Chae; Sangkeun Lee 0001;

Non-parametric single image super resolution

Abstract

In this paper, we introduce a single image super resolution based on non-parametric local information. The basic idea of the proposed method is to use a property, which is inferred by relations between input and its lower resolution images, of an unknown high resolution image. The experimental results show the efficiency of the proposed algorithm compared to a state-of-the-art method. Besides, the proposed method is not only much faster than the compared method but also able to implement in hardware such as digital TVs and smart phones. Therefore, we believe that the proposed method can be a useful tool for super resolution-related fields.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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