IMPROVED DENOISING OF SAR IMAGES CORRUPTED BY SPECKLE NOISE

In this paper an improved speckle noise reduction method is presented based on wavelet transform. A 2D Gaussian function is found to be the best model fitted to the speckle noise pattern cross-section in the logarithmically transformed noisy image. Therefore, a Gaussian low pass filter using a trous algorithm has been used to decompose the image. A Bayesian estimator is applied to the wavelet coefficients of the logarithmically transformed image to estimate the best value for the noise-free signal. This estimation is based on alpha-stable and Gaussian distribution hypotheses for wavelet coefficients of the signal and noise, respectively. Quantitative and qualitative comparisons of the results obtained by the ew method with the results achieved from the other speckle noise reduction techniques demonstrate its higher performance for speckle reduction in SAR images.

Keywords:

a trous algorithm , alpha-stable distribution , Bayesian estimator , coiflet , SAR image , speckle noise , wavelet