Iterative Relaxed Collaborative Representation With Adaptive Weights Learning for Noise Robust Face Hallucination
文献类型：期刊论文
| 作者 | Liu, Licheng1; Li, Shutao1; Chen, C. L. Philip2,3,4 |
| 刊名 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
 |
| 出版日期 | 2019-05-01 |
| 卷号 | 29期号:5页码:1284-1295 |
| 关键词 | Relaxed collaborative representation face hallucination locality regularization adaptively weights learning noise robust coding |
| ISSN号 | 1051-8215 |
| DOI | 10.1109/TCSVT.2018.2829758 |
| 通讯作者 | Liu, Licheng(lichenghnu@gmail.com) ; Li, Shutao(shutao_li@hnu.edu.cn) |
| 英文摘要 | In recent years, the collaborative representation (CR)-based techniques have been widely employed for face hallucination. However, the conventional CR model becomes less efficient in handling noisy low-resolution face images. In this paper, an iterative relaxed CR (iRCR) model with adaptive weights learning is presented to enhance the resolution of face images corrupted by noise. The core idea of iRCR is that a diagonal weight matrix is incorporated into the objective function, which helps to debase the influence of noise in representation. Different from existing collaborative methods with reweighting strategy where the weights require manually tuning, the weights in iRCR are adaptively learned to stay more consistent with the model error. Moreover, considering the local manifold structure property and nonlocal prior of small patches, the locality regularization and collaborative regularization are incorporated into a unified framework. This enables the proposed iRCR not only to capture the true topology structure of patch manifold but also to exploit the meaningful patterns among the whole training samples for reconstruction. Experimental results on both face dataset and real-world images demonstrate the superiority of our proposed method over several state-of-the-art face hallucination methods. |
| WOS关键词 | IMAGE SUPERRESOLUTION ; SPARSE REPRESENTATION ; RECOGNITION ; ALGORITHM ; EQUATIONS ; SYSTEMS ; MODEL |
| 资助项目 | National Natural Science Foundation of China[61702169] ; National Natural Science Foundation of China[61572540] ; National Natural Science Foundation of China[61751202] ; National Natural Science Fund of China for International Cooperation and Exchanges[61520106001] ; Fundamental Research Funds for the Central Universities[531107050878] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000467063100005 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; National Natural Science Fund of China for International Cooperation and Exchanges ; Fundamental Research Funds for the Central Universities |
| 源URL | [http://ir.ia.ac.cn/handle/173211/24589]  |
| 专题 | 离退休人员 |
| 通讯作者 | Liu, Licheng; Li, Shutao |
| 作者单位 | 1.Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China 2.Univ Macau, Fac Sci & Technol, Macau 999078, Peoples R China 3.Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Licheng,Li, Shutao,Chen, C. L. Philip. Iterative Relaxed Collaborative Representation With Adaptive Weights Learning for Noise Robust Face Hallucination[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2019,29(5):1284-1295. |
| APA | Liu, Licheng,Li, Shutao,&Chen, C. L. Philip.(2019).Iterative Relaxed Collaborative Representation With Adaptive Weights Learning for Noise Robust Face Hallucination.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,29(5),1284-1295. |
| MLA | Liu, Licheng,et al."Iterative Relaxed Collaborative Representation With Adaptive Weights Learning for Noise Robust Face Hallucination".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 29.5(2019):1284-1295. |
入库方式： OAI收割
来源：自动化研究所
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