Benchmarking Framework for SAR Despeckling

NL-SAR: A Unified Nonlocal Framework for Resolution-Preserving (Pol)(In)SAR Denoising

“…This method produces a strong variance reduction with excellent preservation of smallest details, see figure 7(d). It can be considered as the best speckle reduction method for intensity images to date [63]. Some artefacts can be noticed on some discontinuities with artificial edges created parallel to the actual edges.…”

Sensitivity analysis of a scattering-based nonlocal means Despeckling Algorithm

“…The despeckling capabilities of the filter are quantitatively evaluated computing both full-reference and no-reference proper synthetic performance parameters. In particular, the signal-to-noise ratio (SNR), the variance of ratio (VoR), the coefficient of variation (C x ) and the mean structural similarity index measure (MSSIM) are evaluated, as described in Di Martino et al (2014a) and Wang et al (2004). For what concerns SNR and MSSIM, the graphs reported in the following show both the absolute value and the relative value normalized to the maximum.…”

“…group of pixels) in order to reduce speckle effects. So far, the most promising techniques can be arguably considered the nonlocal-means-based and wavelet-based approaches Di Martino et al (2014a), Deledalle et al (2009), Parrilli et al (2012). The nonlocal framework introduces a novel and interesting similarity criterion based on statistical concepts rather than geometrical ones.…”

A Physical Approach for SAR Speckle Simulation: First Results

“…A reliable statistical characterization of the speckle is of key importance for a huge set of applications, e.g. model-based despeckling [Di Martino et al, 2012a, 2013a and segmentation [Collins and Allan, 2009]. Therefore, a key parameter for the statistical characterization of the speckle is the number of independent scatterers per resolution cell, N. Under the hypothesis that N>>1, the central limit theorem can be applied giving rise to a Gaussian complex circular process, with an Exponential distributed intensity and a phase uniformly distributed in (0.2π).…”

“…Therefore, it is crucial to have efficient tools able to predict the SAR data behaviour as a function of the scene parameters. As a matter of fact, the use of a SAR simulator can provide value-added information for SAR data interpretation and a support for SAR processing techniques (e.g., image despeckling [Di Martino et al, 2012a, 2013a, segmentation [Lee and Jurkevich, 1989;Collins and Allan, 2009], change detection , sea target (and extended target) detection [Watts et al, 1990;Tello et al, 2007]). In this paper a SAR simulator able to provide images presenting the appropriate speckle statistics is introduced.…”