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TitleSegmentation of textured polarimetric SAR scenes by likelihood approximation
 
AuthorBeaulieu, J -M; Touzi, R
SourceIEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers) vol. 42, no. 10, 2004 p. 2063-2072, https://doi.org/10.1109/TGRS.2004.835302
Image
Year2004
Alt SeriesEarth Sciences Sector, Contribution Series 2005013
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectsremote sensing; statistical methods; models; textures
Illustrationsgraphs; radar image; digital images
AbstractA hierarchical stepwise optimization process is developed for polarimetric synthetic aperture radar image segmentation. We show that image segmentation can be viewed as a likelihood approximation problem. The likelihood segment merging criteria are derived using the multivariate complex Gaussian, the Wishart distribution, and the K-distribution. In the presence of spatial texture, the Gaussian-Wishart segmentation is not appropriate. The K-distribution segmentation is more effective in textured forested areas. The validity of the product model is also assessed, and a field-adaptable segmentation strategy combining different criteria is examined.
GEOSCAN ID220473

 
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