CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Face Hallucination Via Weighted Adaptive Sparse Regularization
Wang, Zhongyuan1,2; Hu, Ruimin1,2; Wang, Shizheng3; Jiang, Junjun1,2
Source PublicationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
2014-05-01
Volume24Issue:5Pages:802-813
SubtypeArticle
AbstractSparse representation-based face hallucination approaches proposed so far use fixed l(1) norm penalty to capture the sparse nature of face images, and thus hardly adapt readily to the statistical variability of underlying images. Additionally, they ignore the influence of spatial distances between the test image and training basis images on optimal reconstruction coefficients. Consequently, they cannot offer a satisfactory performance in practical face hallucination applications. In this paper, we propose a weighted adaptive sparse regularization (WASR) method to promote accuracy, stability and robustness for face hallucination reconstruction, in which a distance-inducing weighted l(q) norm penalty is imposed on the solution. With the adjustment to shrinkage parameter q, the weighted l(q) penalty function enables elastic description ability in the sparse domain, leading to more conservative sparsity in an ascending order of q. In particular, WASR with an optimal q > 1 can reasonably represent the less sparse nature of noisy images and thus remarkably boosts noise robust performance in face hallucination. Various experimental results on standard face database as well as real-world images show that our proposed method outperforms state-of-the-art methods in terms of both objective metrics and visual quality.
Keywordl(q) Norm Adaptive Sparse Regularization Face Hallucination Super-resolution Weighted Penalty
WOS HeadingsScience & Technology ; Technology
WOS KeywordIMAGE SUPERRESOLUTION ; REPRESENTATION
Indexed BySCI
Language英语
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000336057400008
Citation statistics
Cited Times:40[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8028
Collection模式识别国家重点实验室_生物识别与安全技术研究
Affiliation1.Wuhan Univ, Natl Engn Res Ctr Multimedia Software, Wuhan 430079, Peoples R China
2.Wuhan Univ, Sch Comp, Wuhan 430079, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Zhongyuan,Hu, Ruimin,Wang, Shizheng,et al. Face Hallucination Via Weighted Adaptive Sparse Regularization[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2014,24(5):802-813.
APA Wang, Zhongyuan,Hu, Ruimin,Wang, Shizheng,&Jiang, Junjun.(2014).Face Hallucination Via Weighted Adaptive Sparse Regularization.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,24(5),802-813.
MLA Wang, Zhongyuan,et al."Face Hallucination Via Weighted Adaptive Sparse Regularization".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 24.5(2014):802-813.
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