CASIA OpenIR  > 模式识别国家重点实验室  > 视频内容安全
Exposure fusion via sparse representation and shiftable complex directional pyramid transform
Wang, Jinhua1,2; Wang, Weiqiang1; Li, Bing3; Xu, Guangmei2; Zhang, Ruizhe2; Zhang, Jingzun2
Source PublicationMULTIMEDIA TOOLS AND APPLICATIONS
2017-07-01
Volume76Issue:14Pages:15755-15775
SubtypeArticle
AbstractSparse code theory with the sliding window technique can be used for the efficient fusion of multi-exposure images. However, when the size of the source images is large, this process requires a significant amount of time. To solve this problem, we propose a method that uses low-frequency sub-images of the source images as the input to the sparse code fusion framework. These low-frequency sub-images (which are far smaller than the entire image) provide a coarse representation of the original image. Regarding multi-scale decomposition, the high redundancy ratio of some methods limits their applicability to image fusion, especially multi-exposure image fusion (usually more than two source images). In this paper, we propose a method that employs a novel shiftable complex directional pyramid with shift-invariance and a low redundancy ratio to obtain the low-and high-frequency sub-images. For the high-frequency sub-image, we introduce a novel fusion rule based on the entropy of the segmented block, allowing more details of the source images to be preserved. Experiments show that our method attains results that are comparable to or better than existing methods.
KeywordExposure Fusion Pdtdfb Sparse Representation Fusion Rule
WOS HeadingsScience & Technology ; Technology
DOI10.1007/s11042-016-3868-2
WOS KeywordK-SVD ; IMAGES
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61202245 ; Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges under Beijing Municipality(CITTCD20130513) ; importation and development of High-Caliber Talents Project of Beijing Municipal Institutions(CITTCD20130320) ; Beijing Education Commission Science and Technology Project ; Research on Image Recognition of Seal in Chinese Painting and Calligraphy on Multi-features Fusion(KM201311417015) ; 61271370 ; 61271369 ; 61372148 ; 91420202 ; 61370138)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000404609900024
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15240
Collection模式识别国家重点实验室_视频内容安全
Affiliation1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
2.Beijing Union Univ, Coll Informat Technol, Beijing 100101, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Jinhua,Wang, Weiqiang,Li, Bing,et al. Exposure fusion via sparse representation and shiftable complex directional pyramid transform[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2017,76(14):15755-15775.
APA Wang, Jinhua,Wang, Weiqiang,Li, Bing,Xu, Guangmei,Zhang, Ruizhe,&Zhang, Jingzun.(2017).Exposure fusion via sparse representation and shiftable complex directional pyramid transform.MULTIMEDIA TOOLS AND APPLICATIONS,76(14),15755-15775.
MLA Wang, Jinhua,et al."Exposure fusion via sparse representation and shiftable complex directional pyramid transform".MULTIMEDIA TOOLS AND APPLICATIONS 76.14(2017):15755-15775.
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