Before revision:  More specifically, for the nonblind recovery (with known probe in advance), by enforcing the continuity of the overlapping region for the image (sample), the nonlinear optimization model is established based on a novel smooth-truncated amplitude-Gaussian metric .
After revision:  More specifically, for the nonblind recovery (with known probe in advance), by enforcing the continuity of the overlapping region for the image (sample), the nonlinear optimization model is established based on a novel smooth-truncated amplitude-Gaussian metric (ST-AGM). Such metric allows for fast calculation of the proximal mapping with closed form, and meanwhile provides the possibility for the convergence guarantee of the first-order nonconvex optimization algorithm due to its Lipschitz smoothness.