Single Image Super-resolution Reconstruction Method Based on LC-KSVD Algorithm

被引：1
|
作者：
Zhang, Yaolan [1 ]
Liu, Yijun [1 ]
机构：
[1] Sch Guangdong Univ Technol, Guangzhou 510006, Guangdong, Peoples R China
来源：
MATERIALS SCIENCE, ENERGY TECHNOLOGY, AND POWER ENGINEERING I | 2017年 / 1839卷
关键词：
Label consist K-SVD (LC-KSVD); KSVD; sparse representation; super-resolution reconstruction; dictionary learning; REGULARIZATION;
D O I：
10.1063/1.4982460
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
A good dictionary has direct impact to the result of super-resolution image reconstruction. For solving the problem that dictionary learning only contains representation ability but no class information using K-SVD algorithm, this paper proposes single image super-resolution algorithm based on LC-KSVD (Label consist K-SVD). The algorithm adds classifier parameter constraints into the process of dictionary learning and classifier parameters in the process, making the dictionary possess good representation and discrimination ability. The experimental results show that the algorithm has high reconstruction results and good robustness.
引用
收藏
页数：6
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