Improving Level Set Method for Fast Auroral Oval Segmentation | |
Yang, Xi1; Gao, Xinbo1; Tao, Dacheng2,3; Li, Xuelong4 | |
刊名 | ieee transactions on image processing |
2014-07-01 | |
卷号 | 23期号:7页码:2854-2865 |
关键词 | Auroral oval segmentation shape knowledge reinitialization lattice Boltzmann method sparse field method |
ISSN号 | 1070-986x |
英文摘要 | auroral oval segmentation from ultraviolet imager images is of significance in the field of spatial physics. compared with various existing image segmentation methods, level set is a promising auroral oval segmentation method with satisfactory precision. however, the traditional level set methods are time consuming, which is not suitable for the processing of large aurora image database. for this purpose, an improving level set method is proposed for fast auroral oval segmentation. the proposed algorithm combines four strategies to solve the four problems leading to the high-time complexity. the first two strategies, including our shape knowledge-based initial evolving curve and neighbor embedded level set formulation, can not only accelerate the segmentation process but also improve the segmentation accuracy. and then, the latter two strategies, including the universal lattice boltzmann method and sparse field method, can further reduce the time cost with an unlimited time step and narrow band computation. experimental results illustrate that the proposed algorithm achieves satisfactory performance for auroral oval segmentation within a very short processing time. |
WOS标题词 | science & technology ; technology |
类目[WOS] | computer science, artificial intelligence ; engineering, electrical & electronic |
研究领域[WOS] | computer science ; engineering |
关键词[WOS] | geodesic active contours ; lattice boltzmann method ; image segmentation ; curve evolution ; models ; propagation ; formulation ; flows ; edges ; gpu |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000337141400008 |
公开日期 | 2015-03-18 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/22376] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Xidian Univ, Sch Elect Engn, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China 2.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia 3.Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Peoples R China |
推荐引用方式 GB/T 7714 | Yang, Xi,Gao, Xinbo,Tao, Dacheng,et al. Improving Level Set Method for Fast Auroral Oval Segmentation[J]. ieee transactions on image processing,2014,23(7):2854-2865. |
APA | Yang, Xi,Gao, Xinbo,Tao, Dacheng,&Li, Xuelong.(2014).Improving Level Set Method for Fast Auroral Oval Segmentation.ieee transactions on image processing,23(7),2854-2865. |
MLA | Yang, Xi,et al."Improving Level Set Method for Fast Auroral Oval Segmentation".ieee transactions on image processing 23.7(2014):2854-2865. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论