Noise reducing phase retrieval

In the context of imaging using the Hanbury Brown-Twiss effect, this paper describes a phase retrieval algorithm capable of producing high-quality images despite large amounts of noise in the coherence magnitude measurement data. Previously the problem was conceived as two distinct steps: coherence magnitude estimation, followed by image construction. The present unified formulation accepts highly noisy data and estimates both the measurement noise and the image using the numerous constraints on the coherence data, the image, and their interrelations. The technique is shown to reduce the necessary imaging time by many orders of magnitude.