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Super Resolution Algorithm using TV-G Decomposition
Kyoung-Bae Eum(엄경배),Dong-Kyu Beom(범동규) 한국디지털콘텐츠학회 2017 한국디지털콘텐츠학회논문지 Vol.18 No.8
Among single image SR techniques, the TV based SR approach seems most successful in terms of edge preservation and no artifacts. But, this approach achieves insufficient SR for texture component. In this paper, we proposed a new TV-G decomposition based SR method to solve this problem. We proposed the SVR based up-sampling to get better edge preservation in the structure component. The NNE used the relaxed constraint to improve the NE. We used the NNE based learning method to improve the resolution of the texture component. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed SR method when comparing with conventional interpolation method, ScSR, TV and NNE.