Multi-distance phase retrieval represents a computational imaging technique that synergizes a basic imaging setup with computational post-processing. This method involves capturing diffraction intensity at distinct distances, enabling the iterative reconstruction of the target's wavefront by incorporating the intensity patterns into the relevant algorithm. Despite the advantages of lensless imaging through multi-distance phase retrieval, including its uncomplicated setup, expansive field of view, and freedom from aberrations, challenges persist in terms of sluggish convergence and limited resolution. To address these concerns, the presented paper introduces enhancements to both the imaging system and the algorithm. This dual approach contributes to a remarkable 5.88 times acceleration in convergence speed, all achieved without the need for supplementary equipment. Moreover, a substantial enhancement in imaging quality is achieved when compared to the conventional method.
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