Results 281 to 290 of about 574,951 (322)
Astigmatic phase retrieval of lightfields with helical wavefronts
, 2012 Clare A. Henderson
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Deep phase retrieval: Analyzing over-parameterization in phase retrieval
Signal Processing, 2021Abstract Phase retrieval aims to recover the phase of a complex-valued signal from magnitude measurements. Recently, approaches based on non-convex optimization which solve the phase retrieval problem directly using gradient descent methods have become more and more popular.
Qi Yu +4 more
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Topical Meeting On Signal Recovery and Synthesis II, 1986
In this review an overview will be given of the state-of-the-art in phase retrieval (PR). PR occurs in many different areas of signal processing: - in imaging, where the image only yields the modulus of the wavefunction in the image plane, while for the reconstruction of the object we also need its phase - in speckle interferometry where we obtain the ...
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In this review an overview will be given of the state-of-the-art in phase retrieval (PR). PR occurs in many different areas of signal processing: - in imaging, where the image only yields the modulus of the wavefunction in the image plane, while for the reconstruction of the object we also need its phase - in speckle interferometry where we obtain the ...
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IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
A direct, noniterative approach to retrieving a multidimensional complex image (i.e., its phase can vary from pixel to pixel) from the magnitude of its Fourier transform is developed. The uniqueness of the reconstruction is shown to be a direct consequence of the existence of zero surfaces or sheets in the multidimensional z transforms of the image ...
R. Lane, W. Fright, R. Bates
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A direct, noniterative approach to retrieving a multidimensional complex image (i.e., its phase can vary from pixel to pixel) from the magnitude of its Fourier transform is developed. The uniqueness of the reconstruction is shown to be a direct consequence of the existence of zero surfaces or sheets in the multidimensional z transforms of the image ...
R. Lane, W. Fright, R. Bates
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Unconventional Optical Imaging II, 2020
Hyperspectral (HS) imaging retrieves information from data obtained across a broad spectral range of spectral channels. The object to reconstruct is a 3D cube, where the two coordinates are spatial and the third one is spectral. We assume that this cube is complex-valued, i.e. characterized spatially-frequency varying amplitude and phase.
Vladimir Y. Katkovnik +2 more
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Hyperspectral (HS) imaging retrieves information from data obtained across a broad spectral range of spectral channels. The object to reconstruct is a 3D cube, where the two coordinates are spatial and the third one is spectral. We assume that this cube is complex-valued, i.e. characterized spatially-frequency varying amplitude and phase.
Vladimir Y. Katkovnik +2 more
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Polarimetric Fourier Phase Retrieval
SIAM Journal on Imaging ScienceszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Julien Flamant +3 more
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Noise reducing phase retrieval
Applied Optics, 2015In the context of imaging using the Hanbury Brown-Twiss effect, this paper describes a phase retrieval algorithm capable of producing high-quality images despite large amounts of noise in the coherence magnitude measurement data. Previously the problem was conceived as two distinct steps: coherence magnitude estimation, followed by image construction ...
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Optical Society of America Annual Meeting, 1990
The problem of reconstructing an object function from the modulus of its Fourier transform arises in many disciplines. Several algorithms have been proposed to solve this problem. One of the most successful of those algorithms is the iterative transform algorithm, but is has a disadvantage in that it stagnates before it reaches a solution in some cases.
H. Garnaoui, A. H. Tewfik
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The problem of reconstructing an object function from the modulus of its Fourier transform arises in many disciplines. Several algorithms have been proposed to solve this problem. One of the most successful of those algorithms is the iterative transform algorithm, but is has a disadvantage in that it stagnates before it reaches a solution in some cases.
H. Garnaoui, A. H. Tewfik
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2010 International Symposium on Optomechatronic Technologies, 2010
Imaging the internal structure of quasi-transparent three-dimensional (3D) objects is one of the most challenging tasks for optical systems. If the light propagates coherently through the volumetric object, then collection of phase projections from different angles and tomographic reconstruction are required.
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Imaging the internal structure of quasi-transparent three-dimensional (3D) objects is one of the most challenging tasks for optical systems. If the light propagates coherently through the volumetric object, then collection of phase projections from different angles and tomographic reconstruction are required.
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