Phase retrieval via conjugate gradient minimization in double-plane lensless holographic microscopy

Abstract

Optimization-based phase retrieval method for digital lensless holographic microscopy in the double-plane recording configuration is proposed. In our method the phase retrieval is framed as an optimization problem that can be efficiently and rigorously tackled with gradient decent tools. This is done with the conjugate gradient method that possesses excellent theoretical features such as global and fast convergence (compared to steepest descent) and relatively low computational cost (compared to second order optimizers). The proposed method is extensively tested with simulations and experimental measurements that show superiority of our method over the Gerchberg-Saxton algorithm, especially in terms of reconstruction of problematic low frequency components of viable phase information.