Speckle noise reduction of airborne SAR images with symmetric Daubechies wavelets

We report the study of a multiresolution speckle reduction method for airborne synthetic aperture radar (SAR) images. The SAR image is first subband-coded using complex symmetric Daubechies wavelets, followed by a noise estimate on the three high-pass bands. An elliptic wavelet coefficient thresholding rule is then applied, that preserves the global orientation of the complex wavelet coefficient distribution. FInally, a multiresolution synthesis (inverse wavelet transform) is done in a last small dim objects. A speckle index is computed to quantify the speckle reduction performance. We compare our results with those obtained using median and geometrical (Crimmins) filters.