Penalized-likelihood image reconstruction for digital holography.
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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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Overview of compressive sensing techniques applied in holography [Invited]
TL;DR: An overview of the theoretical guidelines for application of CS in digital holography and the benefits of compressive digital holographic sensing are provided.
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Convergent incremental optimization transfer algorithms: application to tomography
TL;DR: This paper provides the first convergent OS-type algorithm for (nonconcave) penalized-likelihood (PL) transmission image reconstruction by using separable paraboloidal surrogates (SPS) which yield closed-form maximization steps.
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Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography
Vittorio Bianco,Melania Paturzo,Pasquale Memmolo,Andrea Finizio,Pietro Ferraro,Bahram Javidi +5 more
TL;DR: A fast non-Bayesian denoising method is proposed that avoids this trade-off by means of a numerical synthesis of a moving diffuser and shows a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement.
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Encoding multiple holograms for speckle-noise reduction in optical display.
Pasquale Memmolo,Vittorio Bianco,Melania Paturzo,Bahram Javidi,Paolo A. Netti,Pietro Ferraro +5 more
TL;DR: A new effective method for encoding in a single complex wavefront the contribution of multiple incoherent reconstructions is proposed, thus allowing to obtain a single synthetic digital hologram that show significant speckle-reduction when optically projected by a Spatial Light Modulator (SLM).
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Feature-preserving regularization method for complex-valued inverse problems with application to coherent imaging
TL;DR: The proposed technique produces images where coherent speckle artifacts are effectively suppressed, and important features of the underlying scenes are preserved, and the challenging optimization problems posed in the framework are solved.
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