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Mixture multiscale autoregressive modelling of SAR imagery for segmentation
Wen, XB; Tian, Z
Source PublicationELECTRONICS LETTERS
2003-08-21
Volume39Issue:17Pages:1272-1274
SubtypeArticle
AbstractA new and efficient multiscale model for the segmentation of synthetic aperture radar imagery namely the mixture multiscale autoregressive (MMAR) model, is presented. The estimation of parameters is easily performed via expectation maximisation algorithm. Experimental results of the MMAR model are proposed and compared with those of previous methods.
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Language英语
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000185206100030
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9915
Collection09年以前成果
Affiliation1.Northwestern Polytech Univ, Dept Comp Sci & Technol, Xian 710072, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
3.Northwestern Polytech Univ, Dept Math & Informat Sci, Xian 710072, Peoples R China
4.Chinese Acad Sci, Inst Remote Sensing Applicat, Lab Remote Sensing Informat Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Wen, XB,Tian, Z. Mixture multiscale autoregressive modelling of SAR imagery for segmentation[J]. ELECTRONICS LETTERS,2003,39(17):1272-1274.
APA Wen, XB,&Tian, Z.(2003).Mixture multiscale autoregressive modelling of SAR imagery for segmentation.ELECTRONICS LETTERS,39(17),1272-1274.
MLA Wen, XB,et al."Mixture multiscale autoregressive modelling of SAR imagery for segmentation".ELECTRONICS LETTERS 39.17(2003):1272-1274.
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