Phase-gradient-based initialization for lensless quantitative phase imaging

Quantitative phase imaging of transparent samples with large phase variations is fundamentally challenged by the nonconvex nature of phase retrieval from intensity-only measurements. In this regime, conventional algorithms with random initialization often converge to nonphysical solutions and fail to recover meaningful phase information, even when the forward model is accurately known. Here, we present a phase-gradient-based initialization strategy for coded ptychographic imaging that exploits the fact that local phase gradients remain stably encoded as lateral displacements in coded intensity patterns. By extracting displacement-derived phase-gradient information from measured intensities and constructing a globally consistent initial phase, the proposed initialization introduces essential first-order physical constraints prior to optimization. Simulations and experiments demonstrate that this strategy enables stable and physically correct reconstruction in large-phase regimes where random initialization breaks down, without increasing measurement redundancy.