Abstract

Previous work described a phase retrieval algorithm that accepts highly noisy Fourier modulus data and uses the numerous constraints on the coherence data, the image, and their interrelations to obtain high-quality images. In the context of intensity correlation imaging, computational results have shown that the technique is able to reduce the necessary imaging time by many orders of magnitude. The present paper is a theoretical examination of the algorithm, including the issues of convergence, the properties of the convergent image, and the relation between invariance of the image to random initial conditions and the accuracy of the foreground specification.

© 2016 Optical Society of America

Noise reducing phase retrieval

David C. Hyland
Appl. Opt. 54(33) 9728-9735 (2015)

Mitigating the effect of noise in the hybrid input–output method of phase retrieval

Russell Trahan and David Hyland
Appl. Opt. 52(13) 3031-3037 (2013)

Phase retrieval of images using Gaussian radial bases

Russell Trahan and David Hyland
Appl. Opt. 52(36) 8627-8633 (2013)

Generalized proximal smoothing (GPS) for phase retrieval

Minh Pham, Penghang Yin, Arjun Rana, Stanley Osher, and Jianwei Miao
Opt. Express 27(3) 2792-2808 (2019)

Phase retrieval with complexity guidance

Mansi Butola, Sunaina Rajora, and Kedar Khare
J. Opt. Soc. Am. A 36(2) 202-211 (2019)