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Sparse representation-based demosaicing method for microgrid polarimeter imagery
Zhang JC(张俊超)1,2,3,4,5; Luo HB(罗海波)1,4,5; Liang, Rongguang3; Ahmed, Ashfaq6; Zhang XY(张祥越)1,2,4,5; Hui B(惠斌)1,4,5; Chang Z(常铮)1,4,5
Department光电信息技术研究室
Source PublicationOptics Letters
ISSN0146-9592
2018
Volume43Issue:14Pages:3265-3268
Indexed BySCI ; EI
EI Accession number20182905555509
WOS IDWOS:000438867400018
Funding OrganizationChina Scholarship Council (CSC) ; Thirteenth Five-Year Preresearch Program of China
Abstract

To address the key image interpolation issue in microgrid polarimeters, we propose a machine learning model based on sparse representation. The sparsity and non-local self-similarity priors are used as regularization terms to enhance the stability of an interpolation model. Moreover, to make the best of the correlation among different polarization orientations, patches of different polarization channels are joined to learn adaptive sub-dictionary. Synthetic and real images are used to evaluate the interpolated performance. The experimental results demonstrate that our proposed method achieves state-of-the-art results in terms of quantitative measures and visual quality.

Language英语
WOS SubjectOptics
WOS KeywordFocal-plane Polarimeters ; Interpolation ; Division ; Dictionaries
WOS Research AreaOptics
Funding ProjectChina Scholarship Council (CSC)[201704910730] ; Thirteenth Five-Year Preresearch Program of China[41415020104]
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/22153
Collection光电信息技术研究室
Corresponding AuthorZhang JC(张俊超)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.College of Optical Sciences, University of Arizona, Tucson,AZ 85721, United States
4.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China
5.Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016, China
6.Department of Bioengineering, Hong Kong University of Science and Technology, Hong Kong, China
Recommended Citation
GB/T 7714
Zhang JC,Luo HB,Liang, Rongguang,et al. Sparse representation-based demosaicing method for microgrid polarimeter imagery[J]. Optics Letters,2018,43(14):3265-3268.
APA Zhang JC.,Luo HB.,Liang, Rongguang.,Ahmed, Ashfaq.,Zhang XY.,...&Chang Z.(2018).Sparse representation-based demosaicing method for microgrid polarimeter imagery.Optics Letters,43(14),3265-3268.
MLA Zhang JC,et al."Sparse representation-based demosaicing method for microgrid polarimeter imagery".Optics Letters 43.14(2018):3265-3268.
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