In this paper, we investigate the results of a field-test campaign measuring distributed-volume turbulence using a high-frame-rate digital holographic (DH) sensor. Distributed-volume turbulence, or strong turbulence distributed throughout the propagation path, is particularly challenging for DH systems and limits their...
Tyler J. Hardy, Casey J. Pellizzari· Unconventional Imaging, Sens...· 0 citations
Despite recent progress, our ability to sense and correct deep atmospheric turbulence remains limited. Such turbulence arises from distributed-volume aberrations that produce strong blur, scintillation, and severe anisoplanatism. Conventional approaches typically require a point-source beacon and are limited to sensing...
Casey J. Pellizzari, Tyler J. Hardy, M. Spencer· Unconventional Imaging, Sens...· 0 citations
Digital Holography Model-Based Iterative Reconstruction (DHMBIR) jointly estimates atmospheric phase and target reflectance from noisy holography frames via Expectation-Maximization (EM). High wind speeds decorrelate consecutive frames fast enough to trap deterministic EM in local minima, and real-time wavefront correc...
Dominic A. Flowers, Casey J. Pellizzari, G. Buzzard et al.· Unconventional Imaging, Sens...· 0 citations
This work introduces a training-free framework that combines a spatiotemporal implicit neural representation with an aperture-aware maximum-likelihood formulation to recover dynamic, speckle-free imagery directly from noisy observations, enabling adaptation to arbitrary pupil geometries without retraining.
Matthew R. Ziemann, Casey J. Pellizzari, Tyler J. Hardy et al.· 0 citations
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