A novel super-resolution image and video reconstruction approach based on Newton-Thiele's rational kernel in sparse principal component analysis

doi:10.1007/s11042-016-3557-1

CORC > 合肥物质科学研究院 > 中国科学院合肥物质科学研究院 > 中科院合肥智能机械研究所

	A novel super-resolution image and video reconstruction approach based on Newton-Thiele's rational kernel in sparse principal component analysis
	He, Lei 1; Tan, Jieqing 1; Huo, Xing 1; Xie, Chengjun 2
刊名	MULTIMEDIA TOOLS AND APPLICATIONS
	2017-04-01
卷号	76 期号:7 页码:9463-9483
关键词	Newton-thiele Super-resolution Linear Minimum Mean Square-error Estimation Sparse Principal Component Analysis
DOI	10.1007/s11042-016-3557-1
文献子类	Article
英文摘要	In this paper, we propose a new image and video sequences reconstruction approach, where the Newton-Thiele's vector valued rational interpolation is combined with the sparse principal component analysis. Through observation of the degraded model, the reconstruction scheme is performed by two steps. Firstly, the sparse principal component analysis and the linear minimum mean square-error estimation method are used to remove the noise from the degraded image. And then, the Newton-Thiele's vector valued rational interpolation is used to magnify the denoising result, by which the details and texture regions of image can be well preserved. By using this novel reconstruction model by Newton-Thiele's rational kernel in sparse principal component analysis, the final reconstructed results not only have good visual effect, but also have rich texture details. In order to show the effectiveness and robustness of the proposed method, we have done plenty of experiments on images and video sequences, and the experimental results show that the proposed method can produce better high-quality resolution results, as compared with the state-of-the-art methods.
WOS关键词	INTERPOLATION ; HALLUCINATION ; REMOVAL
WOS研究方向	Computer Science ; Engineering
语种	英语
WOS记录号	WOS:000399016300016
资助机构	National Natural Science Foundation of China(61472466 ; National Natural Science Foundation of China(61472466 ; National Natural Science Foundation of China(61472466 ; National Natural Science Foundation of China(61472466 ; NSFC-Guangdong Joint Foundation(U1135003) ; NSFC-Guangdong Joint Foundation(U1135003) ; NSFC-Guangdong Joint Foundation(U1135003) ; NSFC-Guangdong Joint Foundation(U1135003) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; 61502141 ; 61502141 ; 61502141 ; 61502141 ; 61070227) ; 61070227) ; 61070227) ; 61070227) ; National Natural Science Foundation of China(61472466 ; National Natural Science Foundation of China(61472466 ; National Natural Science Foundation of China(61472466 ; National Natural Science Foundation of China(61472466 ; NSFC-Guangdong Joint Foundation(U1135003) ; NSFC-Guangdong Joint Foundation(U1135003) ; NSFC-Guangdong Joint Foundation(U1135003) ; NSFC-Guangdong Joint Foundation(U1135003) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Anhui Provincial Natural Science Foundation(1508085QF128) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; Fundamental Research Funds for the Central Universities(JZ2015HGXJ0175) ; 61502141 ; 61502141 ; 61502141 ; 61502141 ; 61070227) ; 61070227) ; 61070227) ; 61070227)
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/31833]
专题	合肥物质科学研究院_中科院合肥智能机械研究所
作者单位	1.Hefei Univ Technol, Sch Comp & Informat, Sch Math, Hefei 230009, Peoples R China 2.Chinese Acad Sci, Inst Intelligent Machines, Hefei, Peoples R China
推荐引用方式 GB/T 7714	He, Lei,Tan, Jieqing,Huo, Xing,et al. A novel super-resolution image and video reconstruction approach based on Newton-Thiele's rational kernel in sparse principal component analysis[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2017,76(7):9463-9483.
APA	He, Lei,Tan, Jieqing,Huo, Xing,&Xie, Chengjun.(2017).A novel super-resolution image and video reconstruction approach based on Newton-Thiele's rational kernel in sparse principal component analysis.MULTIMEDIA TOOLS AND APPLICATIONS,76(7),9463-9483.
MLA	He, Lei,et al."A novel super-resolution image and video reconstruction approach based on Newton-Thiele's rational kernel in sparse principal component analysis".MULTIMEDIA TOOLS AND APPLICATIONS 76.7(2017):9463-9483.