A Fast Dictionary Training Algorithm for Single Image Super-Resolution

被引：1
|
作者：
Lv, Yiliang [1 ]
Liu, Jiwei [1 ]
机构：
[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, 92th Mailbox,30 XueYuan Rd, Beijing, Peoples R China
来源：
PROCEEDINGS OF 2013 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT INFORMATION PROCESSING | 2013年 / 256卷
关键词：
Image super-resolution; Cluster; SVD; Spares representation;
D O I：
10.1007/978-3-642-38466-0_52
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Generally the dictionary for single image super-resolution is trained by iterations of MP algorithm and K-SVD algorithm. Using the dictionary, low resolution images can be restored to high resolution images with high quality. But the training process always takes a lot of time. So in this paper we use SVD to analyze the space relationship between the high and low resolution samples, and present a cluster based algorithm for dictionary training. Compared with the K-SVD based algorithm, the proposed algorithm trains the dictionary with a much higher speed, and restores the images with similar visual quality.
引用
收藏
页码：469 / 476
页数：8
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