Lensfree computational imaging based on multi-distance phase retrieval

Iterative phase retrieval, as a computational imaging technique, provides a powerful tool that combines the superiority of post-processing algorithm with an optical system, which will facilitate a low-cost and portable implementation for microscope. Lensfree imaging based on multi-distance phase retrieval becomes a focused topic in the domain of computational imaging, due to its high-resolution, wide field and aberration-less propertyies. Multi-distance phase retrieval reconstructs a full wavefront merely with a dataset of defocused intensity patterns related to different diffraction distances. At present, this technique suffers from tilt illumination artifact, convergence stagnation, measurement uncertainty of the sample-to-sensor distance, color imaging artifact and resolution loss with pixelated problem. Different correction methods to solve these problems were proposed in this paper. Experiment was also given to validate the performance of these methods.