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arXiv · 1708.01142

Phase-error estimation and image reconstruction from digital-holography data using a Bayesian framework

Casey J. Pellizzari·Mark F. Spencer·Charles A. Bouman
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Abstract

The estimation of phase errors from digital-holography data is critical for applications such as imaging or wave-front sensing. Conventional techniques require multiple i.i.d. data and perform poorly in the presence of high noise or large phase errors. In this paper we propose a method to estimate isoplanatic phase errors from a single data realization. We develop a model-based iterative reconstruction algorithm which computes the maximum a posteriori estimate of the phase and the speckle-free object reflectance. Using simulated data, we show that the algorithm is robust against high noise and strong phase errors.

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Casey J. Pellizzari, Mark F. Spencer, Charles A. Bouman. 2017-06-09. Phase-error estimation and image reconstruction from digital-holography data using a Bayesian framework. https://doi.org/10.1364/josaa.34.001659

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