DocumentCode :
461595
Title :
Robust Despeckle for SAR Image Using Multiscale Autoregressive Model
Author :
Wen, Xianbin ; Zhang, Hua ; Tian, Zheng
Author_Institution :
Dept. of Comput. Sci. & Eng., Tianjin Univ. of Technol.
Volume :
1
fYear :
2006
fDate :
16-20 2006
Abstract :
We propose a novel, robust and multiscale despeckling method, based on the robust multiscale scale-recursive estimation algorithm of multiscale autoregressive (MAR) model on dyadic tree. First, a suitable MAR model, which provide a powerful framework for describing random process and fields that evolve in scale, is selected to model SAR image. Then, filtering for the image is given based on the robust scale-recursive optimal estimation algorithm. The proposed algorithm is not only computationally efficient but also capable of generating error statistics, as desired. Experiments over SAR images confirm the robustness of the filtering algorithm we proposed
Keywords :
autoregressive processes; error statistics; filtering theory; radar imaging; random processes; synthetic aperture radar; SAR image; dyadic tree; error statistics; filtering algorithm; multiscale autoregressive model; multiscale despeckling method; random process; robust multiscale scale-recursive estimation algorithm; robust scale-recursive optimal estimation algorithm; Computer science; Equations; Filtering algorithms; Filters; Noise measurement; Random processes; Robustness; Spatial resolution; Speckle; Synthetic aperture radar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
Type :
conf
DOI :
10.1109/ICOSP.2006.344511
Filename :
4128847
Link To Document :
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