DocumentCode :
2844825
Title :
High Resolution SAR Images Multi-Layer Segmentation Based on Graph Partitioning
Author :
Liu Ai-Ping ; Liu Zhong ; Fu Kun ; You Hong-jian
Author_Institution :
Electron. Eng. Coll., Navy Eng. Univ., Wuhan, China
fYear :
2009
fDate :
19-20 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
A method based on multi-scale inherited information for SAR image segmentation is proposed. This method combines image´s macroscopical and microcosmical features together, introducing the traditional single scale processing technique into the dynamic changing multi-scale analyzed framework, which makes it easy to obtain image essential features. Anisotropic diffusion equation is adopted to get multi-scale images sequences. From coarser scale to finer scale inherited graph partitioning strategy is used, for coarser scale is easy to be segmented and the segmentation results can lead finer scale segmentation. The experimental results on real high resolution SAR images demonstrate the merit of proposed method. Moreover, this method can fulfill the request of different image processing task, and consists with people´s cognizing process and vision process system.
Keywords :
image segmentation; radar computing; radar imaging; synthetic aperture radar; SAR image multilayer segmentation; anisotropic diffusion equation; inherited graph partitioning strategy; macroscopical features; microcosmical features; multiscale image sequences; multiscale inherited information; single scale processing; synthetic aperture radar; vision process system; Anisotropic magnetoresistance; Equations; Image analysis; Image processing; Image resolution; Image segmentation; Image sequence analysis; Machine vision; Multiresolution analysis; Synthetic aperture radar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
Type :
conf
DOI :
10.1109/ICIECS.2009.5365016
Filename :
5365016
Link To Document :
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