Speckle Reduction in Matrix-Log Domain for Synthetic Aperture Radar Imaging

Synthetic aperture radar (SAR) images are widely used for Earth observation to complement optical imaging. By combining information on the polarization and phase shift of echos, SAR offer high sensitivity geometry materials that compose a scene. This richness comes with drawback inherent all coherent imaging modalities: strong signal-dependent noise called “speckle.” paper addresses mathematical issues performing speckle reduction in transformed domain: matrix-log domain. Rather than directly estimating noiseless covariance matrices, recasting denoising problem terms matrices stabilizes fluctuations makes it possible apply off-the-shelf algorithms. We refine method MuLoG by replacing heuristic procedures exact expressions improving estimation strategy. corrects bias original should facilitate encourage adaptation general-purpose processing methods