Preliminary results on soil moisture mapping in Alessandria area (Northern Italy) using Envisat A-SAR

This work present some experimental campaigns aiming to assess the potential of monitoring soil moisture by ENVISAT ASAR (Advanced Synthetic Aperture Radar). Soil moisture measurements were carried out on November 2003 and June 2004 close to Alessandria (Northern Italy) by using a TDR probe simultaneously to ENVISAT overpasses. In situ measurements had been collected in agricultural fields that were subsequently identified on ENVISAT ASAR images by means of a geo-coding process. Pixels of each area have been averaged in order to compute the mean backscattering coefficient. Results have been derived concerning the sensitivity of the backscattering coefficient to soil-moisture compared to what is predicted by a semi-empirical scattering model

Locally Adaptive DCT Filtering for Signal-Dependent Noise Removal

This work addresses the problem of signal-dependent noise removal in images. An adaptive nonlinear filtering approach in the orthogonal transform domain is proposed and analyzed for several typical noise environments in the DCT domain. Being applied locally, that is, within a window of small support, DCT is expected to approximate the Karhunen-Loeve decorrelating transform, which enables effective suppression of noise components. The detail preservation ability of the filter allowing not to destroy any useful content in images is especially emphasized and considered. A local adaptive DCT filtering for the two cases, when signal-dependent noise can be and cannot be mapped into additive uncorrelated noise with homomorphic transform, is formulated. Although the main issue is signal-dependent and pure multiplicative noise, the proposed filtering approach is also found to be competing with the state-of-the-art methods on pure additive noise corrupted images