  It was recently shown that the phase retrieval imaging of a sample can be
modeled as a simple convolution process. Sometimes, such a convolution depends
on physical parameters of the sample which are difficult to estimate a priori.
In this case, a blind choice for those parameters usually lead to wrong
results, e.g., in posterior image segmentation processing. In this manuscript,
we propose a simple connection between phase-retrieval algorithms and
optimization strategies, which lead us to ways of numerically determining the
physical parameters
