A Markov-modeled maximum likelihood estimator for multi-look holographic reconstruction achieves near-ideal performance under strong inter-look speckle correlation by outperforming methods that assume independence.
Coherent plug-and-play: digital holographic imaging through atmospheric turbulence using model-based iterative reconstruction and convo- lutional neural networks
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Maximum Likelihood Reconstruction for Multi-Look Digital Holography with Markov-Modeled Speckle Correlation
A Markov-modeled maximum likelihood estimator for multi-look holographic reconstruction achieves near-ideal performance under strong inter-look speckle correlation by outperforming methods that assume independence.