Genetic Algorithm Phase Retrieval for the Systematic Image‐Based Optical Alignment Test Bed

Taylor, J.; King, Beth; Steincamp, Jim; Rakoczy, John

doi:10.1086/498827

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…In this article we make a step further proposing a new hybrid stochastic approach to better explore the phase solution space through a smart use of Genetic Algorithms (GAs) 15 . GAs have been already applied to the phase problem in different fields 16 17 18 19 . The novelty of our new approach consists in the development of a Memetic Algorithm (MA) 20 in the context of phase retrieval applied to CDI; this scheme represents a natural choice for a smart merging of stochastic and deterministic optimization methods: the algorithm has been developed hybridizing a GA, which guarantees a wide exploration of the configuration space, with local optimization algorithms like Hybrid Input-Output and Error Reduction.…”

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confidence: 99%

Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms

Colombo¹,

Galli²,

De³

et al. 2017

Sci Rep

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Coherent Diffractive Imaging is a lensless technique that allows imaging of matter at a spatial resolution not limited by lens aberrations. This technique exploits the measured diffraction pattern of a coherent beam scattered by periodic and non-periodic objects to retrieve spatial information. The diffracted intensity, for weak-scattering objects, is proportional to the modulus of the Fourier Transform of the object scattering function. Any phase information, needed to retrieve its scattering function, has to be retrieved by means of suitable algorithms. Here we present a new approach, based on a memetic algorithm, i.e. a hybrid genetic algorithm, to face the phase problem, which exploits the synergy of deterministic and stochastic optimization methods. The new approach has been tested on simulated data and applied to the phasing of transmission electron microscopy coherent electron diffraction data of a SrTiO 3 sample. We have been able to quantitatively retrieve the projected atomic potential, and also image the oxygen columns, which are not directly visible in the relevant high-resolution transmission electron microscopy images. Our approach proves to be a new powerful tool for the study of matter at atomic resolution and opens new perspectives in those applications in which effective phase retrieval is necessary.Full-field and scanning microscopes can be either lens-based or lensless imaging systems. Coherent Diffractive Imaging (CDI) is a lensless technique that permits imaging matter at a spatial resolution not limited by lens aberrations. The seminal idea of CDI was due to David Sayre in 1952 1 but it was only experimentally demonstrated for X-rays in 1999 2 and, more recently, also for electrons, using a Transmission Electron Microscope (TEM), giving rise to the Electron Diffractive Imaging (EDI) [3][4][5] .The goal is to retrieve a qualitative/quantitative image of a scattering function related to a physical property of the scattering object, such as the electron density (X-ray CDI) or the atomic potential (EDI). High Resolution TEM (HRTEM) images of the projected atomic potential are phase-contrast images limited by the high-order aberrations of the objective lens, which distort the phase of the scattered wave function, giving rise to images of the sample, which in general are not immediately interpretable in terms of its atomic structure 6 . Instead, diffraction patterns of scattering objects are not affected by these aberrations. Therefore they contain, in principle, undistorted information on the scattering function at a better spatial resolution with respect to lens-based imaging systems 3-5 . The diffracted intensity, for weak-scattering objects, is proportional only to the modulus of the Fourier Transform (FT) of the scattering function. Any phase information, which is experimentally lost (phase problem 1 ), has to be retrieved by means of suitable algorithms. The lensless image of the scattering function, obtained by means of an inverse FT of the diffraction pattern once that the correct phase ...

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confidence: 99%

Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms

Colombo¹,

Galli²,

De³

et al. 2017

Sci Rep

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Simple accurate model‐based phase diversity phase retrieval algorithm for wavefront sensing in high‐resolution optical imaging systems

et al. 2020

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In optical imaging systems, the aberration is an important factor that impedes realising diffraction‐limited imaging. Accurate wavefront sensing and control play important role in modern high‐resolution optical imaging systems nowadays. In this study, a simple model‐based phase retrieval algorithm is proposed for accurate efficient wavefront sensing with high dynamic range. In the authors’ algorithm, a wavefront is represented by the Zernike polynomials, and the Zernike coefficients are solved by the least‐squares‐based non‐linear optimisation method, i.e. the Lederberg–Marquardt algorithm, with multiple phase‐diversity images. The numerical results show that the proposed algorithm is capable of retrieving wavefront with a large dynamic range up to seven wavelength and robust to noise. In comparison, the proposed algorithm is more efficient than the existing model‐based technique and more accurate than existing Fourier ‐ transformation‐based iterative techniques.

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Space vehicle pose estimation via optical correlation and nonlinear estimation

Rakoczy

Herren

2008

SPIE Proceedings

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Genetic Algorithm Phase Retrieval for the Systematic Image‐Based Optical Alignment Test Bed

Cited by 3 publications

References 12 publications

Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms

Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms

Simple accurate model‐based phase diversity phase retrieval algorithm for wavefront sensing in high‐resolution optical imaging systems

Space vehicle pose estimation via optical correlation and nonlinear estimation

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