Image super-resolution reconstruction algorithm based on clustering

doi:10.1109/CCDC.2015.7161915

CORC > 兰州理工大学 > 兰州理工大学

	Image super-resolution reconstruction algorithm based on clustering
	Zhao, Xiaoqiang; Jia, Yunxia
	2015-07-17
会议日期	May 23, 2015 - May 25, 2015
会议地点	Qingdao, China
DOI	10.1109/CCDC.2015.7161915
页码	6144-6148
英文摘要	In view of the single frame image super-resolution reconstruction, this paper combined with sparse representation algorithm is proposed based on clustering image super-resolution reconstruction algorithm. First to sample the input image classification, clustering and for each class of training samples accordingly subdictionaries training, learning, with high and low resolution of the dictionary. Finally using the high resolution image block of dictionary and the product of the sparse representation to the low resolution image reconstruction, the experimental results show that this algorithm can effectively improve the quality of reconstruction image. In this article, through the simulation experiment and compares the traditional interpolation method, Elad method, verified the validity of the algorithm is proposed in this paper. © 2015 IEEE.
会议录	Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
会议录出版者	Institute of Electrical and Electronics Engineers Inc.
语种	中文
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117206]
专题	兰州理工大学
作者单位	College of Electrical and Information Engineering, Lanzhou Univ. of Tech., Lanzhou, China
推荐引用方式 GB/T 7714	Zhao, Xiaoqiang,Jia, Yunxia. Image super-resolution reconstruction algorithm based on clustering[C]. 见:. Qingdao, China. May 23, 2015 - May 25, 2015.