DocumentCode :
796453
Title :
Nonstationary Spatial Texture Estimation Applied to Adaptive Speckle Reduction of SAR Data
Author :
Hondt, Olivier D. ; Ferro-Famil, Laurent ; Pottier, Eric
Author_Institution :
Inst. of Electron. & Telecommun. Lab., Rennes I Univ.
Volume :
3
Issue :
4
fYear :
2006
Firstpage :
476
Lastpage :
480
Abstract :
This letter proposes a new model for the second-order statistics of spatial texture in synthetic aperture radar images. The autocovariance function is locally approximated by a two-dimensional anisotropic Gaussian kernel (AGK) to characterize texture by its local orientation and anisotropy. The estimation of texture parameters at a given scale is based on the gradient structure tensor operator and does not require the explicit computation of the autocovariance. Finally, a new filter called AGK minimum mean square error (MMSE) that takes into account this spatial information is introduced and compared with the refined MMSE filter. The proposed filter has better performance in terms of texture preservation and structure enhancement
Keywords :
covariance analysis; image denoising; image texture; mean square error methods; speckle; synthetic aperture radar; 2D anisotropic Gaussian kernel; AGK minimum mean square error; MMSE filter; SAR data; adaptive speckle reduction; autocovariance function; nonstationary spatial texture estimation; second-order statistics; synthetic aperture radar images; texture analysis; Adaptive filters; Anisotropic magnetoresistance; Clutter; Information filtering; Information filters; Parameter estimation; Reflectivity; Speckle; Statistics; Synthetic aperture radar; Adaptive speckle filter; local orientation estimation; nonstationary spatial covariance; synthetic aperture radar (SAR) texture analysis;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2006.876223
Filename :
1715298
Link To Document :
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