New algorithm for reducing speckle noise in the SAR image
WU Aijing · Journal of Xidian University · 2012
To reduce speckle noise and preserve edge characteristics in synthetic aperture radar(SAR) images,an additive transform noise mode of speckle noise in the SAR image is given and a new algorithm for speckle reduction by the combination of self-snake diffusion and regulated L1-L2 optimization under undecimated wavelet packet transform(uWPT) is proposed.In the new method,a SAR image is first decomposed into multiple subbands by multi-level uWPT.The lowpass subband is filtered by self-snake diffusion,and the subband filtered is regarded as the local mean of the original SAR image in the wavelet domain.Based on the local mean,the adaptive and shrinkage soft-thresholding filter is applied to the remaining subbands by regulated L1-L2 optimization.Finally,the despeckled image is recovered from all of filtered subbands by the inverse uWPT.Experimental results show that compared with the Kuan filter algorithm,the P-M diffusion filter algorithm and the Γ-WMAP algorithm using undecimated wavelet transform,the proposed algorithm has better performance in terms of reducing speckle noise and preserving the edge of SAR images.