Single image super resolution based on sparse representation and adaptive dictionary selection

Single image super resolution based on sparse representation and adaptive dictionary selection
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DOI：
10.1109/icdsp.2014.6900704
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发表时间：
2014-09
期刊：
2014 19th International Conference on Digital Signal Processing
影响因子：
--
通讯作者：
X. Li;Jing Chen;Z. Cui;Minghu Wu;Xiuchang Zhu
X. Li;Jing Chen;Z. Cui;Minghu Wu;Xiuchang Zhu
中科院分区：
其他
文献类型：
--
作者：
X. Li;Jing Chen;Z. Cui;Minghu Wu;Xiuchang Zhu

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An improved single image super resolution based on patch-wise sparse recovery is proposed in this paper. K-SVD is adopted to train a coupled dictionary. Besides, adaptive selection is proposed among dictionaries with different patch size. Simulation results show that the proposed approach provides good subjective quality and up to 0.4 dB PSNR improvement with significant time reduction.