Abstract

New methods are described for forming intensity estimates of randomly moving objects from quantum-limited data. These methods assume a preprocessed data set consisting of photon differences. Image estimates are formed with the use of the method of maximum likelihood. Algorithms for recovering an image from a measurement of its autocorrelation or triple correlation are derived by considering the limit as the photoconversion rate tends toward infinity.

© 1991 Optical Society of America

Image recovery from correlations

Timothy J. Schulz and Donald L. Snyder
J. Opt. Soc. Am. A 9(8) 1266-1272 (1992)

Signal recovery from autocorrelation and cross-correlation data

Timothy J. Schulz and David G. Voelz
J. Opt. Soc. Am. A 22(4) 616-624 (2005)

Least-squares phase recovery from the bispectrum phase: an algorithm for a two-dimensional object

Hiroaki Takajo and Tohru Takahashi
J. Opt. Soc. Am. A 8(7) 1038-1047 (1991)

Uniqueness properties of higher-order autocorrelation functions

John I. Yellott and Geoffrey J. Iverson
J. Opt. Soc. Am. A 9(3) 388-404 (1992)

Noniterative image reconstruction from photon-limited data with the use of self-cross-correlation

Xiaotian Shi and Rabab K. Ward
J. Opt. Soc. Am. A 12(1) 47-57 (1995)