Phase Retrieval for Two-Dimensional Images

Phase retrieval refers to the iterative computational process using the GS (Gerchberg-Saxton) algorithm to recover phase information from two-dimensional images. This technique involves analyzing and processing image data through Fourier transforms and inverse transforms to reconstruct missing phase components, resulting in more accurate image representation. The primary objective of phase retrieval is to enhance image quality and resolution by recovering phase information, leading to more detailed and realistic visual outputs. The iterative algorithm employs repeated cycles of constraint application between spatial and frequency domains, gradually refining and optimizing phase recovery results. Key implementation aspects include: initializing with random phase estimates, applying Fourier transforms to switch between domains, enforcing known constraints (like amplitude measurements), and using inverse transforms to update phase estimates iteratively until convergence criteria are met. This progressive refinement approach significantly improves phase reconstruction accuracy compared to single-pass methods.