Journal ArticleDOI
Phase-retrieval algorithms for a complicated optical system
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TLDR
Improved algorithms permit a more accurate characterization of complicated optical systems from their point spread functions, independent of the number of coefficients or phase points.Abstract:
Phase-retrieval algorithms have been developed that handle a complicated optical system that requires multiple Fresnellike transforms to propagate from one end of the system to the other including the absorption by apertures in more than one plane and allowance for bad detector pixels. Gradient-search algorithms and generalizations of the iterative-transform phase-retrieval algorithms are derived. Analytic expressions for the gradient of an error metric, with respect to polynomial coefficients and with respect to point-by-point phase descriptions, are given. The entire gradient can be computed with the number of transforms required to propagate a wave front from one end of the optical system to the other and back again, independent of the number of coefficients or phase points. This greatly speeds the computation. The reconstruction of pupil amplitude is also given. A convergence proof of the generalized iterative transform algorithm is given. These improved algorithms permit a more accurate characterization of complicated optical systems from their point spread functions.read more
Citations
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Learning approach to optical tomography
Ulugbek S. Kamilov,Ioannis N. Papadopoulos,Morteza H. Shoreh,Alexandre Goy,Cedric Vonesch,Michael Unser,Demetri Psaltis +6 more
TL;DR: A method for imaging 3D phase objects in a tomographic configuration implemented by training an artificial neural network to reproduce the complex amplitude of the experimentally measured scattered light is described.
Journal ArticleDOI
Maximum-likelihood refinement for coherent diffractive imaging
TL;DR: In this paper, the authors introduce the application of maximum-likelihood (ML) principles to the image reconstruction problem in coherent diffractive imaging, and describe an implementation of the optimization procedure for ptychography, using conjugate gradients.
Journal ArticleDOI
Phase retrieval algorithms: a personal tour [Invited]
TL;DR: This paper gives the reader a personal tour through the field of phase retrieval and related works that lead up to or cited the paper "Phase Retrieval Algorithms: a Comparison," [Appl. Opt.21, 2758 (1982)].
Journal ArticleDOI
Hubble Space Telescope characterized by using phase-retrieval algorithms
TL;DR: The Cramer-Rao lower bounds show that point spread functions taken well out of focus result in smaller errors when aberrations are estimated and that, for those images, photon noise is not a limiting factor.
Journal ArticleDOI
Diffractive imaging of highly focused X-ray fields
TL;DR: In this article, the authors demonstrate a coherent imaging technique that enables them to image the complex field at the focus of an X-ray zone plate without the need for conventional Xray lenses, and they show that there are no fundamental limits on the resolution of this lensless imaging technique other than the wavelength of the X-rays themselves.
References
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Journal ArticleDOI
Introduction to Fourier Optics
Joseph W. Goodman,Mary E. Cox +1 more
TL;DR: The second edition of this respected text considerably expands the original and reflects the tremendous advances made in the discipline since 1968 as discussed by the authors, with a special emphasis on applications to diffraction, imaging, optical data processing, and holography.
Journal ArticleDOI
Phase retrieval algorithms: a comparison.
TL;DR: Iterative algorithms for phase retrieval from intensity data are compared to gradient search methods and it is shown that both the error-reduction algorithm for the problem of a single intensity measurement and the Gerchberg-Saxton algorithm forThe problem of two intensity measurements converge.
Journal Article
A practical algorithm for the determination of phase from image and diffraction plane pictures
TL;DR: In this article, an algorithm is presented for the rapid solution of the phase of the complete wave function whose intensity in the diffraction and imaging planes of an imaging system are known.
Journal ArticleDOI
Phase-retrieval stagnation problems and solutions
James R. Fienup,C. C. Wackerman +1 more
TL;DR: The iterative Fourier-transform algorithm has been demonstrated to be a practical method for reconstructing an object from the modulus of its Fourier transform (i.e., solving the problem of recovering phase from a single intensity measurement).
Journal ArticleDOI
Hubble Space Telescope characterized by using phase-retrieval algorithms
TL;DR: The Cramer-Rao lower bounds show that point spread functions taken well out of focus result in smaller errors when aberrations are estimated and that, for those images, photon noise is not a limiting factor.