Single image super-resolution via subspace projection and neighbor embedding
文献类型：期刊论文
| 作者 | Xiaoyan Li; Hongjie He; Zhongke Yin; Fan Chen; Jun Cheng |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2014 |
| 英文摘要 | In this paper, we present a novel learning-based single image super-resolution algorithm to address the problems of inefficient learning and improper estimation in coping with nonlinear high-dimensional feature data. Our method named as subspace projection and neighbor embedding (SPNE) first projects the high-dimensional data into two different subspaces respectively, i.e., kernel principal component analysis (KPCA) subspace and modified locality preserving projection (MLPP) subspace to obtain the global and local structures of data. In an optimal low-dimensional feature space, the k-nearest neighbors of each input low-resolution (LR) image patch can be found for efficient learning. Then within similarity measures and proportional factors, the k embedding weights are used to estimate high-frequency information from a training dataset. Finally, we apply iterative back projection (IBP) to further enhance the super-resolution results. Experiments on simulative and actual LR images demonstrate that the proposed approach outperforms the existing NE-based super-resolution methods in terms of visual quality and some selected objective metrics. |
| 收录类别 | SCI |
| 原文出处 | http://ac.els-cdn.com/S092523121400424X/1-s2.0-S092523121400424X-main.pdf?_tid=ca93fd7e-29d3-11e5-903a-00000aacb35d&acdnat=1436842711_c605d1fe821b43f30dfd4329cb7a6a90 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5414]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | NEUROCOMPUTING |
| 推荐引用方式 GB/T 7714 | Xiaoyan Li,Hongjie He,Zhongke Yin,et al. Single image super-resolution via subspace projection and neighbor embedding[J]. NEUROCOMPUTING,2014. |
| APA | Xiaoyan Li,Hongjie He,Zhongke Yin,Fan Chen,&Jun Cheng.(2014).Single image super-resolution via subspace projection and neighbor embedding.NEUROCOMPUTING. |
| MLA | Xiaoyan Li,et al."Single image super-resolution via subspace projection and neighbor embedding".NEUROCOMPUTING (2014). |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。