Denoising of single look complex SAR images using Hurst estimation
Corina Naforniţa, Alexandru Isar, James D. B. Nelson · 2016
SAR roughness images acquired by satellites are affected by speckle noise. We propose a denoising method based on semi-local estimation of the Hurst exponent in the wavelet domain. To estimate the Hurst parameter, we consider low resolution coefficients to be relatively free of noise. The high resolution level coefficients are most affected by noise and their energy is corrected according to the estimated parameter. The algorithm is tested on ESA Sentinel-1 data single look images. In our experiments, we used the discrete wavelet transform and the dual-tree complex wavelet transform. The denoising system proposed is anisotropic and realizes a performant treatment of the homogeneous regions; the degree of oversmoothing can be adjusted by the number of decomposition levels used in the denoising process.