TY - GEN
T1 - A low-complexity MMSE Bayesian estimator for suppression of speckle in SAR images
AU - Damseh, Rafat R.
AU - Ahmad, M. Omair
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/29
Y1 - 2016/7/29
N2 - In synthetic aperture radar (SAR) images, speckle noise reduction is a crucial pre-processing step for their successful interpretation and thus has drawn a great deal of attention of researchers in the image processing community. The Bayesian estimation is a powerful signal estimation technique and has been widely used for speckle noise removal in images. In this work, a low complexity wavelet-based Bayesian estimation technique for despeckling of images is developed. The main idea of the proposed technique is in establishing suitable statistical models for the wavelet coefficients and then in using these models to develop a shrinkage function with a low-complexity realization for the estimation of the wavelet coefficients of the noise-free images. The experimental results demonstrate the effectiveness of the proposed despeckling scheme in providing a significant reduction in the speckle noise at a very low computational cost and simultaneously preserving the image details.
AB - In synthetic aperture radar (SAR) images, speckle noise reduction is a crucial pre-processing step for their successful interpretation and thus has drawn a great deal of attention of researchers in the image processing community. The Bayesian estimation is a powerful signal estimation technique and has been widely used for speckle noise removal in images. In this work, a low complexity wavelet-based Bayesian estimation technique for despeckling of images is developed. The main idea of the proposed technique is in establishing suitable statistical models for the wavelet coefficients and then in using these models to develop a shrinkage function with a low-complexity realization for the estimation of the wavelet coefficients of the noise-free images. The experimental results demonstrate the effectiveness of the proposed despeckling scheme in providing a significant reduction in the speckle noise at a very low computational cost and simultaneously preserving the image details.
KW - image despeckling
KW - MMSE Bayesian estimation
KW - statistical model of image wavelet coefficients
KW - Synthetic aperture radar (SAR) image
KW - wavelet shrinkage
UR - http://www.scopus.com/inward/record.url?scp=84983403933&partnerID=8YFLogxK
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U2 - 10.1109/ISCAS.2016.7527412
DO - 10.1109/ISCAS.2016.7527412
M3 - Conference contribution
AN - SCOPUS:84983403933
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 1002
EP - 1005
BT - ISCAS 2016 - IEEE International Symposium on Circuits and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016
Y2 - 22 May 2016 through 25 May 2016
ER -