DocumentCode :
2294016
Title :
SAR Image Despeckling Using Local Contextual Hidden Markov Model in the Contourlet Domain
Author :
Wang, Shuang ; Xu, Xiao ; Hou, Biao ; Jiao, Li Cheng
Author_Institution :
Inst. of Intelligent Inf. Process., Xidian Univ., Xi´´an
fYear :
2006
fDate :
16-19 Oct. 2006
Firstpage :
1
Lastpage :
4
Abstract :
Synthetic aperture radar (SAR) image despeckling is an important problem in the SAR applications. A novel despeckling approach using a local contextual hidden Markov model (LCHMM) in the contourlet domain is presented in this paper. The proposed method can not only use the multiresolution and multidirection characteristics of the contourlet transform, but also exploit the local statistics and capture the intrascale dependencies of the contourlet coefficients by using LCHMM. The experiments in despeckling SAR images show that the proposed method in contrary to other methods can obtain a better trade-off between smoothing the homogeneous areas and keeping the edges and can get better visual effect
Keywords :
hidden Markov models; image denoising; image resolution; radar imaging; radar resolution; speckle; synthetic aperture radar; LCHMM; SAR image despeckling; contourlet transform; local contextual hidden Markov model; multiresolution characteristics; synthetic aperture radar; Context modeling; Filter bank; Hidden Markov models; Multiresolution analysis; Radar signal processing; Signal resolution; Smoothing methods; Statistics; Synthetic aperture radar; Wavelet transforms; SAR image despeckling; a local contextual hidden Markov model; contourlet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar, 2006. CIE '06. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-9582-4
Electronic_ISBN :
0-7803-9583-2
Type :
conf
DOI :
10.1109/ICR.2006.343462
Filename :
4148463
Link To Document :
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