Forest parameter estimation in the Pol-InSAR context employing the multiplicative–additive speckle noise model

This paper addresses the problem of speckle noise on single baseline polarimetric SAR interferometry (Pol-InSAR) on the basis of the multiplicative–additive speckle noise model. Considering this speckle noise model, a novel filtering technique is defined and studied in terms of simulated and experimental Pol-InSAR data. As demonstrated, the use of the multiplicative–additive speckle noise model does not lead to a corruption of the useful information but to an improvement of its estimation. The performance of the algorithm is analyzed in terms of the physical parameters retrieved from the filtered data, that in this work correspond to the forest height and the ground phase. In case of experimental data, the retrieved forest height is compared and validated against Lidar ground truth measurements.