Title :
Bayesian approach to SAR image reconstruction
Author :
Walessa, M. ; Datcu, M.
Author_Institution :
Remote Sensing Data Center, German Aerosp. Res. Establ., Wessling, Germany
Abstract :
An approach for reconstruction of speckled SAR images is presented. This approach is based upon Bayes´ rule obtaining the maximum a posteriori estimate of the underlying radar cross section. The prior used for the reconstruction is modelled by Gibbs random fields reflecting the existing texture characteristics, while the system transfer function of the SAR signal processing together with the speckle noise is accounted for by the likelihood distribution. The solution of this optimization problem is obtained by relaxation methods such as simulated annealing using the prior information as a constraint to limit the optimization space
Keywords :
Bayes methods; geophysical signal processing; geophysical techniques; image reconstruction; image texture; radar imaging; remote sensing by radar; simulated annealing; speckle; synthetic aperture radar; Bayes method; Bayesian approach; Gibbs random field; SAR; geophysical measurement technique; image processing; image reconstruction; image restoration; image texture; land surface; likelihood distribution; maximum a posteriori estimate; optimization problem; radar imaging; radar remote sensing; relaxation method; signal processing; simulated annealing; speckle; speckle noise; synthetic aperture radar; system transfer function; terrain mapping; underlying radar cross section; Bayesian methods; Constraint optimization; Image reconstruction; Maximum a posteriori estimation; Radar cross section; Radar signal processing; Relaxation methods; Simulated annealing; Speckle; Transfer functions;
Conference_Titel :
Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International
Print_ISBN :
0-7803-3836-7
DOI :
10.1109/IGARSS.1997.615251
