基于贝叶斯框架的数字全息数据的相位误差估计和图像重建
Phase-error estimation and image reconstruction from digital-holography data using a Bayesian framework
摘要：
从数字全息数据中估计相位误差对于成像或波前传感等应用至关重要。常规技术需要多个i.i.d.在高噪声或大相位误差的情况下，在本文中，我们提出了一种方法来估计等晕相位误差从一个单一的数据实现。我们开发了一种基于模型的迭代重建算法，计算相位和无斑点物体反射率的最大后验估计。仿真结果表明，该算法对强噪声和强相位误差具有较好的鲁棒性。
英文摘要：
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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