SUPER-RESOLUTION USING NEURAL NETWORKS BASED ON THE OPTIMAL RECOVERY THEORY
by
Yizhen Huang
| Citations: | 1 - 1 self |
BibTeX
@MISC{Huang_super-resolutionusing,
author = {Yizhen Huang},
title = {SUPER-RESOLUTION USING NEURAL NETWORKS BASED ON THE OPTIMAL RECOVERY THEORY},
year = {}
}
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Abstract
An optimal recovery based neural-network Super Resolution algorithm is developed. The proposed method is computationally less expensive and outputs images with high subjective quality, compared with previous neuralnetwork or optimal recovery algorithms. It is evaluated on classical SR test images with both generic and specialized training sets, and compared with other state-of-the-art methods. Results show that our algorithm is among the state-of-the-art, both in quality and efficiency. 1.
