Learning phase diversity for solving ill-posed inverse problems in imaging
This work observes that in both incoherent and coherent optical imaging, the irradiance patterns corresponding to two phase diverse measurements associated with the same test object have implicit local correlations, which may be learned by a suitable deep network.