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Solving Phase Retrieval with a Learned Reference
European Conference on Computer Vision, 2020Fourier phase retrieval is a classical problem that deals with the recovery of an image from the amplitude measurements of its Fourier coefficients. Conventional methods solve this problem via iterative (alternating) minimization by leveraging some prior
Rakib Hyder, Zikui Cai, M. Salman Asif
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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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IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019
The classical problem of phase retrieval arises in various signal acquisition systems. Due to the ill-posed nature of the problem, the solution requires assumptions on the structure of the signal.
Rakib Hyder +3 more
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The classical problem of phase retrieval arises in various signal acquisition systems. Due to the ill-posed nature of the problem, the solution requires assumptions on the structure of the signal.
Rakib Hyder +3 more
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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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Fundamental Limits of Weak Recovery with Applications to Phase Retrieval
Annual Conference Computational Learning Theory, 2017In phase retrieval, we want to recover an unknown signal $${{\varvec{x}}}\in {{\mathbb {C}}}^d$$x∈Cd from n quadratic measurements of the form $$y_i = |\langle {{\varvec{a}}}_i,{{\varvec{x}}}\rangle |^2+w_i$$yi=|⟨ai,x⟩|2+wi, where $${{\varvec{a}}}_i\in {{
Marco Mondelli, A. Montanari
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Performance of Phase Retrieval via Phaselift and Quadratic Inversion in Circular Scanning Case
IEEE Transactions on Antennas and Propagation, 2019The reconstruction of the field radiated by a source from square amplitude-only data falls into the realm of phase retrieval. In this paper, we tackle the phase retrieval with two different approaches.
R. Moretta, R. Pierri
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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.
openaire +1 more source