DocumentCode :
3352369
Title :
MVM based SAR image processing for ship pose estimation
Author :
Duan, Chong-Wen ; Hu, Wei-Dong ; Du, Xiao-Yong
Author_Institution :
ATR Key Lab., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2010
fDate :
25-30 July 2010
Firstpage :
1605
Lastpage :
1608
Abstract :
As an essential approach of SAR image interpretation, a good pose estimation calls for two conditions: an accurate extraction of the scattering centers and a thorough exploration of the structural information among them. The article focuses on these two topics successively. Firstly, the power spectrum estimation methods are recommended to improve the scattering center resolution and the Minimum Variance Method (MVM) is chosen for its sidelobe suppressing ability and signal model independence. With the segmented MVM image, the axis extraction problem is then solved by a new strategy, namely the Angle Entropy of Radon transform (AER) strategy. Data from computational electromagnetics are used for experiments. It is shown that the MVM image shows better morphologic feature than the Fourier ones (both original and Hanning-windowed), and the AER strategy achieves more accurate and robust estimation compared with the edge-based Hough transform (HT) technique.
Keywords :
Radon transforms; electromagnetic wave scattering; feature extraction; image resolution; image segmentation; marine radar; oceanographic techniques; pose estimation; radar imaging; radar resolution; ships; synthetic aperture radar; AER strategy; MVM based SAR image processing; MVM image segmentation; angle entropy of Radon transform; axis extraction problem; computational electromagnetics; minimum variance method; morphologic feature; power spectrum estimation; scattering center extraction; scattering center resolution; ship pose estimation; sidelobe suppressing ability; signal model independence; structural information; Azimuth; Clutter; Estimation; Image segmentation; Marine vehicles; Minimization; Scattering; Radon transform; SAR ship image; angle entropy; minimum variance method; pose estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
ISSN :
2153-6996
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2010.5652598
Filename :
5652598
Link To Document :
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