L-hypersurface Based Parameters Selection in Composite Regularization Models with Application to SAR and TomoSAR Imaging

Composite regularization models are widely used in sparse signal processing, making multiple pa-rameters selection a significant problem to be solved. Variety kinds of composite microwave imaging, including ℓ 1 and xmlns:xlink="http://www.w3.org/1999/xlink">2 penalty, nonconvex TV combined dictionary, etc. In this article, new adaptive parameters method named L-hypersurface is proposed. The effectiveness the pro-posed verified by experiments. Simulation experiments indicate that selected optimal have satisfied reconstruction results, both visually numerically. Furthermore, on Gaofen-3 SAR satellite data also exploited show performance proposed method.