DocumentCode
3062498
Title
Non-zero mean statistical models for urban area polarization SAR images
Author
Wenjin Wu ; Huadong Guo ; Xinwu Li ; Jie Chen ; Yixing Ding
Author_Institution
Inst. of Remote Sensing & Digital Earth, Beijing, China
fYear
2013
fDate
21-26 July 2013
Firstpage
2562
Lastpage
2564
Abstract
Urban area man-made target detection based on SAR images has been a challenging field for years due to the complicated scattering mechanisms of dense buildings and the poor visual quality of SAR images caused by speckle noises. To overcome the effect of speckle noise, a substantial portion of SAR image processing methods are based on statistical characteristics. In this paper, the importance of using non-zero mean models is discussed in the experiments, and two statistical models are proposed for polarization SAR image processing. Moreover, a non-zero mean index is invented to test the scattering determinacy level. This work will be very helpful for the improvement of urban area information extraction based on fully polarized SAR images.
Keywords
buildings (structures); object detection; radar imaging; radar polarimetry; remote sensing by radar; speckle; statistical analysis; synthetic aperture radar; terrain mapping; dense buildings; fully polarized SAR images; nonzero mean index; nonzero mean statistical models; polarization SAR image processing methods; poor visual quality; scattering determinacy level; scattering mechanisms; speckle noises; statistical characteristics; urban area information extraction; urban area man-made target detection; Covariance matrices; Gaussian distribution; Indexes; Scattering; Synthetic aperture radar; Urban areas; Vectors; Image analysis; Object recognition; Radar remote sensing; Synthetic aperture radar; Urban areas;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location
Melbourne, VIC
ISSN
2153-6996
Print_ISBN
978-1-4799-1114-1
Type
conf
DOI
10.1109/IGARSS.2013.6723345
Filename
6723345
Link To Document