DocumentCode :
1962869
Title :
Based on Spectrum Cluster High Resolution Remote Sensing Image Multi-criterion Stochastic Tree Division
Author :
Zhihua, Hu ; Jiping, Niu
Author_Institution :
Inst. of Uncertain Syst., Huanggang normal Univ., Huanggang
Volume :
3
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
1039
Lastpage :
1042
Abstract :
The high score pigtail rate satellite remote sensing image may provide the rich data for the urban quakeproof disaster reduction information system´s construction. But, because its slight information is specially rich, has brought certain difficulty for the related terrain feature object detection and the extraction. The image division´s goal lies in the original image divides some in the space neighboring, the spectrum similar homogeneity region. Applies in view of the spectrum cluster in the remote sensing image division when the power moment spectrum calculates with difficulty actual problem, has defined the picture element and the kind of between distance, gives a sampling number theorem, has designed an image lamination division algorithm.
Keywords :
feature extraction; geophysical signal processing; number theory; object detection; pattern clustering; remote sensing; trees (mathematics); feature extraction; image lamination division algorithm; multicriterion stochastic tree division; object detection; pigtail rate satellite remote sensing image; sampling number theorem; spectrum cluster high resolution remote sensing image; urban quakeproof disaster reduction information system construction; Algorithm design and analysis; Computer vision; Data mining; Image resolution; Image sampling; Lamination; Object detection; Remote sensing; Satellites; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.1187
Filename :
4722520
Link To Document :
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