Penalized-likelihood image reconstruction for digital holography.
TLDR
A new numerical reconstruction approach using a statistical technique that reconstructs the complex field of the object from the real-valued hologram intensity data and derives an optimization transfer algorithm that monotonically decreases the cost function at each iteration.Abstract:
Conventional numerical reconstruction for digital holography using a filter applied in the spatial-frequency domain to extract the primary image may yield suboptimal image quality because of the loss in high-frequency components and interference from other undesirable terms of a hologram. We propose a new numerical reconstruction approach using a statistical technique. This approach reconstructs the complex field of the object from the real-valued hologram intensity data. Because holographic image reconstruction is an ill-posed problem, our statistical technique is based on penalized-likelihood estimation. We develop a Poisson statistical model for this problem and derive an optimization transfer algorithm that monotonically decreases the cost function at each iteration. Simulation results show that our statistical technique has the potential to improve image quality in digital holography relative to conventional reconstruction techniques.read more
Citations
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Compressive holography
David J. Brady,Sehoon Lim +1 more
TL;DR: This work demonstrates single frame 3D tomography from 2D holographic data using compressed sampling, which enables signal reconstruction using less than one measurement per reconstructed signal value.
Journal ArticleDOI
Complex-wave retrieval from a single off-axis hologram.
TL;DR: A new digital two-step reconstruction method for off-axis holograms recorded on a CCD camera that is sufficiently general to be applied to sophisticated optical setups that include a microscope objective.
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Strategies for reducing speckle noise in digital holography
Vittorio Bianco,Pasquale Memmolo,Marco Leo,Silvio Montresor,Cosimo Distante,Melania Paturzo,Pascal Picart,Bahram Javidi,Pietro Ferraro +8 more
TL;DR: A broad discussion about the noise issue in DH is provided, with the aim of covering the best-performing noise reduction approaches that have been proposed so far and quantitative comparisons among these approaches will be presented.
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Inline hologram reconstruction with sparsity constraints.
TL;DR: This Letter suggests the use of a sparsity-promoting prior, verified in many inline holography applications, and presents a simple iterative algorithm for 3D object reconstruction under sparsity and positivity constraints.
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Inverse-problem approach for particle digital holography: accurate location based on local optimization.
TL;DR: In this article, the authors proposed a microparticle localization scheme in digital holography based on the inverse-problems approach, which yields the optimal particle set that best models the observed hologram image and resolves this global optimization problem by conventional particle detection followed by a local refinement for each particle.
References
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