Bayesian wavelet shrinkage with edge detection for SAR image despeckling Academic Article

abstract

• In this paper, we present a wavelet-based despeckling method for synthetic aperture radar images and derive a Bayesian wavelet shrinkage factor to estimate noise-free wavelet coefficients. To preserve edges during despeckling, we apply a modified ratio edge detector to the original image and use the obtained edge information in our despeckling framework. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test images.

authors

• Loguinov, Dmitri

published proceedings

• IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

altmetric score

• 3

author list (cited authors)

• Dai, M., Peng, C., Chan, A. K., & Loguinov, D.

citation count

• 122

complete list of authors

• Dai, M||Peng, C||Chan, AK||Loguinov, D

publication date

• August 2004

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Geoscience and Remote Sensing  Journal

keywords

• Minimum Mean Square Error (mmse) Estimation
• Ratio Edge Detector
• Stationary Wavelet Transform (swt)
• Wavelet Shrinkage

Digital Object Identifier (DOI)

• 10.1109/TGRS.2004.831231

start page

• 1642

end page

• 1648

volume

• 42

issue

• 8

URL

• http://dx.doi.org/10.1109/tgrs.2004.831231