红外技术Issue(9)：736-739,4.
基于自训练字典学习的单幅图像的超分辨率重建
Single Image Super-resolution Reconstruction Based on Self-learning Dictionary
张强 1张爱梅 1王华敏 1陈鹏1
作者信息
- 1. 郑州大学机械工程学院，河南 郑州 450001
- 折叠
摘要
Abstract
Based on the self-learning dictionary, a super-resolution reconstruction method of single image is proposed. First of all, according to the image degradation model, the low-resolution image input is processed with blurred and downsampled operations. Then the dictionary is trained with K-SVD method, and we obtain the priori knowledge for reconstruction. Finally, the high-resolution image is reconstructed based on the priori knowledge. The result of simulation experiment shows that the method is superior to conventional methods in the visual effects and objective evaluation, and the time efficiency of the algorithm is also significantly improved.关键词
超分辨率重建/稀疏表示/自训练字典学习/K-SVDKey words
super-resolution reconstruction/sparse representation/self-learning dictionary/K-SVD分类
信息技术与安全科学引用本文复制引用
张强,张爱梅,王华敏,陈鹏..基于自训练字典学习的单幅图像的超分辨率重建[J].红外技术,2015,(9):736-739,4.
