Single Image Super Resolution Based on Sparse Representation and Adaptive Dictionary Selection

被引：0
|
作者：
Fu, Chang-Hong [1 ]
Chen, Hongli [1 ]
Zhang, Hongbin [1 ]
Chan, Yui-Lam [2 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing, Jiangsu, Peoples R China
[2] Hong Kong Polytech Univ, Dept Elect & Informat Engn, Hong Kong, Hong Kong, Peoples R China
来源：
2014 19TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP) | 2014年
关键词：
super resolution; sparse representation; dictionary learning; K-svd; adpative dictionary selection;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：449 / 453
页数：5
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