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Applications of computer holography
Published in Tomoyoshi Shimobaba, Tomoyoshi Ito, Computer Holography, 2019
Tomoyoshi Shimobaba, Tomoyoshi Ito
Holography records the complex amplitude of an object light in interference fringes by interfering with an object light and a reference light. Apart from holography, as shown in Figure 5.1, techniques for recovering the complex amplitude of the object light using only the diffraction patterns of the object light and known information without using interference have been studied. This technique is called the phase retrieval algorithm [115]. Since the phase retrieval algorithm was originally developed in the field of measurement, it is compatible with digital holography. In addition, by using the phase retrieval algorithm framework in hologram calculation, it can also be used for optimizing holograms with better image quality and holograms with higher diffraction efficiency. In this way, the phase retrieval algorithm is an important technique in computer holography. Here, we introduce several phase retrieval algorithms.
Planar Near-Field Measurement and Array Diagnostics
Published in D. G. Fang, Antenna Theory and Microstrip Antennas, 2017
In the conventional near-field measurement, both the amplitude and the phase should be measured. However, in some cases the phase information is either unavailable or erroneous. The prohibitive costof vector measurement equipment and high frequency measurements are two examples of applications in which phaseless near-field antenna measurements through phase retrieval methods may be attractive. The phase retrieval algorithm is based on an iterative Fourier method. The procedural steps required for executing this algorithm are depicted in Figure 8.6[19] where AUT denotes antenna under test. The algorithm requires near-field amplitude measurements on two planes (steps 1 and 2) which are separated by just a few wavelengths. A geometric description of the AUT’s aperture plane, also commonly referred to as the objector aperture constraint, is also required. The amplitude data on each measurement plane and the AUT constraint comprise the inputs to the Fourier iteration (steps 3 − 6) used for the phase retrieval. The productof the Fourier iteration is the complex near-field distribution on the AUT aperture plane and each of the two measurement planes. The Fourier iteration ensures, assuming successful retrieval of the phase, that the complex field distribution on these three planes are related by the Fourier transform. This relationship allows the far-field pattern of the AUT to be computed from the complex field distribution on any one of these three planes (step 7), using standard planar near-field techniques.
Wavefront Slope Measurements in Optical Testing
Published in Daniel Malacara-Hernández, Brian J. Thompson, Advanced Optical Instruments and Techniques, 2017
Alejandro Cornejo-Rodríguez, Alberto Cordero-Davila, Fermín S. Granados Agustín
For testing astronomical telescopes or for using them with adaptive optics devices, Roddier [104] developed a method to find the phase retrieval from wavefront irradiance measurements. Figure 2.28 shows what Roddier called the curvature sensor, because the aim was to obtain irradiance data at the two off-focus planes, P1 and P2, and obtain the phase of the wavefront coming from the optical system.
Phase retrieval based on difference map and deep neural networks
Published in Journal of Modern Optics, 2021
Baopeng Li, Okan K. Ersoy, Caiwen Ma, Zhibin Pan, Wansha Wen, Zongxi Song, Wei Gao
Many physical measurement systems only measure the power spectral density, such as the magnitude square of the Fourier transform of the original signal [1]. A camera takes a picture, which only measures the magnitude information, because CCD or CMOS only measures the light intensity, and phase information is lost. Phase retrieval, which is also called phase recovery or restoration from magnitude, is the recovery of the phase of a constrained signal from the magnitude of its Fourier transform [2,3]. Research on phase retrieval has a long history in many areas. Phase retrieval exists in a number of fields such as astronomy [4], optical imaging [5], X-ray crystallography [6], speech processing [7], blind deconvolution [8] and so on. Recent developments of phase retrieval can be found in the review papers [1,5].
On the characterizations of solutions to perturbed l1 conic optimization problem
Published in Optimization, 2019
Yong-Jin Liu, Ruonan Li, Bo Wang
Sparse Phase Retrieval. Phase retrieval has been an active research topic for decades in various applications such as optical imaging, astronomy and crystallography, which aims at recovering a complex-valued signal from the magnitude squared of M linear measurements (usually corrupted with additive noise ): where the measurement vectors are known, and for the complex-valued number z, denotes its magnitude. To deal with the phase retrieval problem, the following non-convex optimization problem [5] or its variants [6, 7] are often proposed to balance between the sum of squared error and the prior sparsity information of the original signal: where is a regularization parameter. Obviously, the above non-convex optimization problem can be reformulated as the form of Problem (2).
Phase retrieval for studying the structure of vitreous floaters simulated in a model eye
Published in Journal of Modern Optics, 2021
Varis Karitans, Sergejs Fomins, Maris Ozolinsh
In the current study, we are simulating experimentally vitreous floaters in a model eye and develop a method and an optical system for determining the structure of the vitreous floaters based on phase retrieval. Previously, we have used a model eye with a microfluidics system to simulate vitreous floaters [9]. Phase retrieval deals with recovering the phase of the diffracted field and hence also the diffracting object from intensity-only measurements. Phase retrieval seems to be suited for studying the structure of vitreous floaters as they are almost pure phase objects. As far as we know, phase retrieval has never been used to study the structure of objects causing entoptic phenomena of an eye.