Open AccessAN ADAPTIVE SAR IMAGE DESPECKLING ALGORITHM USING STATIONARY WAVELET TRANSFORM
Author(s) -
Amlan Das,
Abhijit Talukdar,
Kandarpa Kumar Sarma
Publication year - 2013
Publication title -
international journal of electronic signal and systems
Language(s) - English
Resource type - Journals
ISSN - 2231-5969
DOI - 10.47893/ijess.2013.1136
Subject(s) - speckle noise , maximum a posteriori estimation , wavelet , wavelet transform , noise (video) , estimator , artificial intelligence , speckle pattern , stationary wavelet transform , pattern recognition (psychology) , computer science , algorithm , rayleigh distribution , synthetic aperture radar , mathematics , discrete wavelet transform , probability density function , statistics , image (mathematics) , maximum likelihood
In this paper, we present a Stationary Wavelet Transform (SWT) based method for the purpose of despeckling the Synthetic Aperture radar (SAR) images by applying a maximum a posteriori probability (MAP) condition to estimate the noise free wavelet coefficients. The solution of the MAP estimator is based on the assumption that the wavelet coefficients have a known distribution. Rayleigh distribution is used for modeling the speckle noise and Laplacian distribution for modeling the statistics of the noise free wavelet coefficients for the purpose of designing the MAP estimator. Rayleigh distribution is used for modeling the speckle noise since speckle noise can be well described by it. The parameters required for MAP estimator is determined by the technique used for parameter estimation after SWT. The experimental results show that the proposed despeckling algorithm efficiently removes speckle noise from the SAR images.