计算机工程2012，Vol.38Issue(20)：191-194,4.DOI:10.3969/j.issn.1000-3428.2012.20.049
基于L1/2正则化的超分辨率图像重建算法
Super-resolution Image Reconstruction Algorithm Based on L1/2 Regularization
摘要
Abstract
In order to improve the image reconstruction quality, by studying the super-resolution image reconstruction technology and the theory of sparse representation, this paper proposes a super-resolution image reconstruction algorithm based on L1/2 regularization. It applies L1/2 regularization into dictionary learning, and reconstructs super-resolution images using learned dictionaries. Experimental results show that the reconstruction results in this paper are better than the results of super-resolution image reconstruction algorithm based on L1 regularization.关键词
L1/2正则化/稀疏表示/超分辨率图像重建/K-SVD算法/字典学习/训练样本Key words
L1/2 regularization/ sparse representation/ super-resolution image reconstruction/ K-SVD algorithm/ dictionary learning/ training sample分类
信息技术与安全科学引用本文复制引用
王欢,王永革..基于L1/2正则化的超分辨率图像重建算法[J].计算机工程,2012,38(20):191-194,4.基金项目
国家自然科学基金资助项目(10801007) （10801007）
国家“973”计划基金资助项目(2010CB731900) （2010CB731900）
