|
|||||
|
|
| 基于稀疏表示的自适应图像超分辨率重建算法 | |
| 引用本文： | 张 垚,徐 斌,周尚波,郑 坚.基于稀疏表示的自适应图像超分辨率重建算法[J].计算机应用研究,2013,30(3):938-941. |
| 作者姓名： | 张 垚 徐 斌 周尚波 郑 坚 |
| 作者单位： | 1. 1. 重庆大学 计算机学院, 重庆 400030; 2. 重庆大学 信息物理社会教育部重点实验室, 重庆 400030 2. 重庆市涪陵区职业教育中心 语言教研组,重庆,408100 3. 重庆大学 计算机学院,重庆,400030 |
| 基金项目： | 国家自然科学基金资助项目（611103114） |
| 摘 要： | 针对图像高分辨率重建过程中稀疏解的存在性和唯一性问题以及超分辨率图像的边缘特征和平滑噪声的关系进行了研究, 提出了局部正则化参数自适应选取的方法。结合联合构造字典的算法, 在重建过程中动态调整正则化参数。通过对图像的超分辨率实验证明, 改进的算法具有较高的可行性, 能有效平衡超分辨率图像的边缘特征和平滑噪声两者的关系, 与传统的超分辨率重建算法相比, 有更高的峰值信噪比。 |
| 关 键 词： | 超分辨率 自适应正则化 联合字典 |
Image super-resolution with adaptive regularization sparse representation |
|
| ZHANG Yao,XU Bin,ZHOU Shang-bo,ZHENG Jian.Image super-resolution with adaptive regularization sparse representation[J].Application Research of Computers,2013,30(3):938-941. | |
| Authors: | ZHANG Yao XU Bin ZHOU Shang-bo ZHENG Jian |
| Affiliation: | 1. a. School of Computer, b. Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing 400030, China; 2. Chinese Teaching & Research Group, Chongqing City Fuling District Occupedion Education Center, Chongqing 408100, China |
| Abstract: | Conduct research on the existence and uniqueness of sparse resolution in super-resolution image reconstruction and the relationship of edge feature and smoothing noise of super-resolution image. In order to solve these problems, this paper proposed the mean of adaptive regularization. Combining with joint over-complete dictionary, it realized dynamically adjust the regularization parameter. Through super-resolution image reconstruction experiment, it demonstrates that this algorithm is working efficiently and balances edge features and smoothing noise well, which has high PSNR compared with the traditional algorithm. |
| Keywords: | super-resolution adaptive regularization joint dictionary |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
| 点击此处可从《计算机应用研究》浏览原始摘要信息 | |
| 点击此处可从《计算机应用研究》下载全文 | |