Speckle reduction of SAR images using wavelet-domain hidden Markov models

Author

Sveinsson, Johannes R. ; Benediktsson, Jon Atli

Author_Institution

Eng. Res. Inst., Iceland Univ., Reykjavik, Iceland

Volume

4

fYear

2000

fDate

2000

Firstpage

1666

Abstract

Wavelet-domain hidden Markov models (HMMs), proposed bu M. S. Crouse et al. (1998), are used for speckle reduction of SAR images. The method is a frameworks for statistical signal processing and is based on HMM and wavelets. The HMM is a tree-structured probabilistic graph that captures the statistical properties of the coefficients of the wavelet transform. Both wavelet and translation-invariant wavelet denoising based on HMMs are studied. Results on denoising of SAR images are presented. The proposed method shows great promise for speckle removal and hence provides good detection performance for SAR based recognition

Keywords

geophysical signal processing; geophysical techniques; hidden Markov models; radar imaging; remote sensing by radar; speckle; synthetic aperture radar; terrain mapping; wavelet transforms; SAR; SAR based recognition; SAR image; geophysical measurement technique; hidden Markov model; land surface; radar imaging; radar remote sensing; speckle reduction; statistical signal processing; synthetic aperture radar; terrain mapping; translation-invariant wavelet denoising; tree-structured probabilistic graph; wavelet transform; wavelet-domain; wavelets; Additive noise; Discrete wavelet transforms; Hidden Markov models; Image edge detection; Noise reduction; Signal processing; Speckle; Tree graphs; Wavelet coefficients; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.857306

Filename

857306