A new wavelet-based method for despeckling SAR images
In this paper, a wavelet-based despeckling method is proposed for suppressing speckle noise in synthetic aperture radar (SAR) images. A new threshold is proposed to classify the wavelet coefficients into significant and insignificant ones. Local statistic in the wavelet domain is used to further classify the significant coefficients into the edge and non-edge coefficients. The edge coefficients remain unaltered, whereas the non-edge and the insignificant ones are reduced in magnitude. Experiments are carried out on a noise-free image corrupted with simulated speckle noise, and a real SAR image. The results show that the proposed method provides a performance better than that of other methods in terms of the peak signal-to-noise ratio and ability to suppress speckle in the homogeneous areas. In addition, it introduces a bias that is much smaller than that of the other methods as well as preserves edges quite well.