TY - GEN
T1 - SAR image denoising
T2 - 14th International Conference on Digital Signal Processing, DSP 2002
AU - Achim, A.
AU - Bezerianos, A.
AU - Tsakalides, P.
N1 - Publisher Copyright:
© 2002 IEEE.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2002
Y1 - 2002
N2 - Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. It appears sensible to reduce speckle in SAR images, provided that the structural features and textural information are not lost. We present a novel speckle removal algorithm within the framework of wavelet analysis. First, we show that the subband decompositions of logarithmically transformed SAR images are best described by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we design a maximum a posteriori (MAP) estimator that exploits this a priori information. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data, and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to a current state-of-the-art soft thresholding technique applied on an aerial image and we quantify the achieved performance improvement.
AB - Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. It appears sensible to reduce speckle in SAR images, provided that the structural features and textural information are not lost. We present a novel speckle removal algorithm within the framework of wavelet analysis. First, we show that the subband decompositions of logarithmically transformed SAR images are best described by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we design a maximum a posteriori (MAP) estimator that exploits this a priori information. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data, and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to a current state-of-the-art soft thresholding technique applied on an aerial image and we quantify the achieved performance improvement.
UR - http://www.scopus.com/inward/record.url?scp=84948683675&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84948683675&partnerID=8YFLogxK
U2 - 10.1109/ICDSP.2002.1028316
DO - 10.1109/ICDSP.2002.1028316
M3 - Conference contribution
AN - SCOPUS:84948683675
T3 - International Conference on Digital Signal Processing, DSP
SP - 1235
EP - 1238
BT - 2002 14th International Conference on Digital Signal Processing Proceedings, DSP 2002
A2 - Skodras, A.N.
A2 - Constantinides, A.G.
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 July 2002 through 3 July 2002
ER -