IGSNRR OpenIR
Millimeter-Wave Ultrahigh Resolution SAR Image Classification Based on a New Feature Set
Wu, Wenjin1; Li, Xinwu1; Guo, Huadong1; Liang, Lei2
2018-08-01
Source PublicationIEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN1545-598X
Volume15Issue:8Pages:1204-1208
Corresponding AuthorLi, Xinwu(lixw@radi.ac.cn)
AbstractAiming at the problems and prospects in millimeter-wave ultrahigh resolution synthetic aperture radar applications, we have developed a method with a new feature set for sophisticated classification of large images. It includes innovative parameters derived from different kinds of spectral and characteristic signatures, such as the correlation signature, radial spectrum, and angular spectrum. These features can mine repetitive information from the fragmented patterns and enhance the texture description in different aspects. In the experiment, the proposed feature set achieves 89% overall accuracy which is 25% higher compared with the gray-level co-occurrence matrix feature set. The four new features contribute to over 50% of the accuracy improvement with a significant increase of the accuracy for vehicles and show a fair performance for all the categories.
KeywordFeature extraction image classification ultra-high resolution (UHR) synthetic aperture radar (SAR)
DOI10.1109/LGRS.2018.2830794
Indexed BySCI
Language英语
Funding ProjectYoung Scientists Fund of the National Natural Science Foundation of China[41601361] ; Director Program through RADI, CAS[Y6SJ1700CX]
Funding OrganizationYoung Scientists Fund of the National Natural Science Foundation of China ; Director Program through RADI, CAS
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000440204900014
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/54510
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLi, Xinwu
Affiliation1.Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Wu, Wenjin,Li, Xinwu,Guo, Huadong,et al. Millimeter-Wave Ultrahigh Resolution SAR Image Classification Based on a New Feature Set[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2018,15(8):1204-1208.
APA Wu, Wenjin,Li, Xinwu,Guo, Huadong,&Liang, Lei.(2018).Millimeter-Wave Ultrahigh Resolution SAR Image Classification Based on a New Feature Set.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,15(8),1204-1208.
MLA Wu, Wenjin,et al."Millimeter-Wave Ultrahigh Resolution SAR Image Classification Based on a New Feature Set".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 15.8(2018):1204-1208.
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