Wavefront Sensing the 3D Image Reconstruction in Deep Turbulence PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Wavefront Sensing the 3D Image Reconstruction in Deep Turbulence PDF full book. Access full book title Wavefront Sensing the 3D Image Reconstruction in Deep Turbulence by Matthais Thomas Banet. Download full books in PDF and EPUB format.
Author: Matthais Thomas Banet Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
"The work presented in this dissertation explores the use of several unconventional imaging and wavefront sensing modalities in the presence of distributed-volume, or "deep," atmospheric turbulence. This dissertation focuses on the propagation of coherent light from laser sources through the atmosphere, and imaging/wavefront sensing at optical and infrared laser wavelengths. Such wavelengths are negatively affected by deep turbulence. We use a coherent detection method known as digital holography to (1) coherently image distant objects and (2) to sense and correct for aberrations due to turbulence along the propagation path. We showed that compensated-beacon adaptive optics can be used with a digital holographic wavefront sensor or a Shack-Hartmann wavefront sensor to improve the performance of beam projection to distant objects over uncompensated beacon adaptive optics. We saw performance gains of 17% for the Shack-Hartmann wavefront sensor and 26% for the digital holographic wavefront sensor on average for several turbulence scenarios. We explored multi-wavelength 3D imaging with digital holography along with two speckle decorrelation mechanisms that degrade 3D imaging performance in a theoretical framework. Upon establishing this framework, we simulated multi-wavelength 3D imaging of distant objects through deep turbulence and reconstructed the imagery using sharpness metric maximization for 3D data. The results showed that the reconstruction process was more successful if using more corrective phase screens along the digital propagation path. Additionally we showed that sharpness metric maximization suffered in performance in the presence of scintillated illumination patterns, also known as uplink scintillation. Finally we explored motion compensated, multi-wavelength 3D imaging with digital holography and a pilot tone in theory. Our theoretical framework predicted that one would see increased noise in range images, known as range chatter, over highly-sloped object facets relative to the optical axis, and simulations bore this out explicitly. We showed that range chatter increases as a function of object facet slope, optical illumination bandwidth, optical frequency spacing, and turbulence. Going further we used sharpness metric maximization to improve the range chatter that was brought about by turbulence."--Pages xiv-xv.
Author: Matthais Thomas Banet Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
"The work presented in this dissertation explores the use of several unconventional imaging and wavefront sensing modalities in the presence of distributed-volume, or "deep," atmospheric turbulence. This dissertation focuses on the propagation of coherent light from laser sources through the atmosphere, and imaging/wavefront sensing at optical and infrared laser wavelengths. Such wavelengths are negatively affected by deep turbulence. We use a coherent detection method known as digital holography to (1) coherently image distant objects and (2) to sense and correct for aberrations due to turbulence along the propagation path. We showed that compensated-beacon adaptive optics can be used with a digital holographic wavefront sensor or a Shack-Hartmann wavefront sensor to improve the performance of beam projection to distant objects over uncompensated beacon adaptive optics. We saw performance gains of 17% for the Shack-Hartmann wavefront sensor and 26% for the digital holographic wavefront sensor on average for several turbulence scenarios. We explored multi-wavelength 3D imaging with digital holography along with two speckle decorrelation mechanisms that degrade 3D imaging performance in a theoretical framework. Upon establishing this framework, we simulated multi-wavelength 3D imaging of distant objects through deep turbulence and reconstructed the imagery using sharpness metric maximization for 3D data. The results showed that the reconstruction process was more successful if using more corrective phase screens along the digital propagation path. Additionally we showed that sharpness metric maximization suffered in performance in the presence of scintillated illumination patterns, also known as uplink scintillation. Finally we explored motion compensated, multi-wavelength 3D imaging with digital holography and a pilot tone in theory. Our theoretical framework predicted that one would see increased noise in range images, known as range chatter, over highly-sloped object facets relative to the optical axis, and simulations bore this out explicitly. We showed that range chatter increases as a function of object facet slope, optical illumination bandwidth, optical frequency spacing, and turbulence. Going further we used sharpness metric maximization to improve the range chatter that was brought about by turbulence."--Pages xiv-xv.
Author: Robert L. Johnson Publisher: ISBN: Category : Languages : en Pages : 82
Book Description
The optical quality of a coherent beam passing through a turbulent flow layer can be severely degraded by phase errors. The principle goal of this research is to model the use of wavefront sensor measurements and computed tomography to reconstruct refractive index distributions of transparent objects for the study of turbulent flows. Tomography is the processing of measurements of one-dimensional line integrals through a two-dimensional function to reconstruct a two-dimensional estimate of the function. A least-squares wavefront phase reconstructor is modeled using Zernike polynomials and triangle functions as elementary functions for the reconstructor. Two tomographic reconstruction algorithms are implemented: (1) iterative reconstruction and (2) filtered back-projection. Through numerical simulation, the effects of undersampling and limited wavefront sensor resolution are studied. Distorted wavefront data are generated by performing line integrals through known objects with different numbers and ranges of view angle. Wavefront reconstruction is applied using varying resolution. Two tomographic reconstruction methods are employed and comparisons are made with the original known objects. Results show that a least-squares wavefront reconstructor using triangle functions provides better results. Increasing the number and range of view angles generally improves the quality of the tomographic reconstruction. Furthermore, iterative tomographic reconstruction techniques prove superior when limited data are available. Optical tomography, Computed tomography, Wavefront reconstruction, Flow visualization, Three-dimensional reconstruction.
Author: Michael C. Roggemann Publisher: CRC Press ISBN: 1351439316 Category : Technology & Engineering Languages : en Pages : 320
Book Description
Learn how to overcome resolution limitations caused by atmospheric turbulence in Imaging Through Turbulence. This hands-on book thoroughly discusses the nature of turbulence effects on optical imaging systems, techniques used to overcome these effects, performance analysis methods, and representative examples of performance. Neatly pulling together widely scattered material, it covers Fourier and statistical optics, turbulence effects on imaging systems, simulation of turbulence effects and correction techniques, speckle imaging, adaptive optics, and hybrid imaging. Imaging Through Turbulence is written in tutorial style, logically guiding you through these essential topics. It helps you bring down to earth the complexities of coping with turbulence.
Author: Robert K. Tyson Publisher: CRC Press ISBN: 1000531368 Category : Technology & Engineering Languages : en Pages : 606
Book Description
Principles of Adaptive Optics describes the foundations, principles, and applications of adaptive optics (AO) and its enabling technologies. This leading textbook addresses the fundamentals of AO at the core of astronomy, high-energy lasers, biomedical imaging, and optical communications. Key Features: Numerous examples to explain and support the underlying principles Hundreds of new references to support the topics that are addressed End-of-chapter questions and exercises A complete system design example threaded through each chapter as new material is introduced
Author: Publisher: ISBN: Category : Languages : en Pages : 13
Book Description
On June 1, 2005 AFOSR awarded a grant to Michigan Technological University to investigate image reconstruction, wave front sensing, and adaptive optics in extreme imaging conditions. This is the final report for this program. The overall goal was to understand imaging under conditions where seeing is exceedingly poor, such as for space surveillance of objects at very low elevation angles, and during daytime hours. In these situations, scintillation and small isoplanatic angles dominate the image measurement and reconstruction problems. Our work was focused on performing trade-offs in the adaptive optics control algorithms for imaging under conditions of poor seeing arising from large zenith angles. In particular, we have developed a closed loop simulation of an adaptive optics system which is physically similar to the AEOS system, that uses the conventional least squares reconstructor, the exponential reconstruction, and the so-called "slope discrepancy" reconstructor. We have also examined the use of the stochastic parallel gradient descent (SPGD) algorithm for deformable mirror control in problems dominated by scintillation and anisoplanatism, and conducted a laboratory experiment to demonstrate this idea. In this report we document the results. Our work with maximum likelihood-based image reconstruction algorithms has been applied to the results provided by the adaptive optics simulation, and representative results are included here.
Author: Stanley H. Chan Publisher: ISBN: 9781638281719 Category : Atmospheric turbulence Languages : en Pages : 0
Book Description
Since the seminal work of Andrey Kolmogorov in the early 19400́9s, imaging through atmospheric turbulence has grown from a pure scientific pursuit to an important subject across a multitude of civilian, space-mission, and national security applications. Fueled by the recent advancement of deep learning, the field is further experiencing a new wave of momentum. However, for these deep learning methods to perform well, new efforts are needed to build faster and more accurate computational models while at the same time maximizing the performance of image reconstruction. The goal of this book is to present the basic concepts of turbulence physics while accomplishing the goal of image reconstruction. Starting with an exploration of optical modeling and computational imaging in Chapter 1, the book continues to Chapter 2, discussing the essential optical foundations required for the subsequent chapters. Chapter 3 introduces a statistical model elucidating atmospheric conditions and the propagation of waves through it. The practical implementation of the Zernike-based simulation is discussed in Chapter 4, paving the way for the machine learning solutions to reconstruction in Chapter 5. In this concluding chapter, classical and contemporary trends in turbulence mitigation are discussed, providing readers with a comprehensive understanding of the field's evolution and a sense of its direction. The book is written primarily for image processing engineers, computer vision scientists, and engineering students who are interested in the field of atmospheric turbulence, statistical optics, and image processing. The book can be used as a graduate text, or advanced topic classes for undergraduates.
Author: Lakhmi C. Jain Publisher: Springer ISBN: 9789811924507 Category : Technology & Engineering Languages : en Pages : 0
Book Description
This book gathers selected papers presented at the conference “Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology,” one of the first initiatives devoted to the problems of 3D imaging in all contemporary scientific and application areas. The two volumes of the book cover wide area of the aspects of the contemporary multidimensional imaging and outline the related future trends from data acquisition to real-world applications based on new techniques and theoretical approaches. This volume contains papers devoted to the theoretical representation and analysis of the 3D images. The related topics included are 3D image transformation, 3D tensor image representation, 3D content generation technologies, 3D graphic information processing, VR content generation technologies, multi-dimensional image processing, dynamic and auxiliary 3D displays, VR/AR/MR device, VR camera technologies, 3D imaging technologies and applications, 3D computer vision, 3D video communications, 3D medical images processing and analysis, 3D remote sensing images and systems, deep learning for image restoration and recognition, neural networks for MD image processing, etc.
Author: Alden S. Jurling Publisher: ISBN: Category : Languages : en Pages : 209
Book Description
"Image-based wavefront sensing via phase retrieval is used to align and characterize optical systems. It was famously used to deduce the prescription error in the Hubble Space Telescope, allowing fabrication of corrective optics. It is being used in ground-based testing of the James Webb Space Telescope (JWST) and is planned for use during JWST's on-orbit commissioning and maintenance. This thesis presents advances in image-based wavefront sensing techniques. Phase retrieval algorithms estimate aberrations of optical systems by using measured point-spread functions (images of unresolved stars), typically at one or more planes through focus, though other measurement schemes are possible. Our nonlinear optimization (NLO) approach to phase retrieval uses a numerical model of the optical system (in terms of the aberration function) and a data consistency error metric. We use a nonlinear optimizer to find the aberration function that best matches the measured data. We describe several advancements within this paradigm. Phase retrieval algorithms rely on a starting estimate; if that estimate is too far from the true solution, the algorithm may never reach a good solution. This problem is particularly serious for segment tips and tilts in segmented aperture telescopes. Extending previous work by S. T. Thurman, we developed a geometrical-optics-based method for estimating segment tips and tilts to produce good starting estimates for phase retrieval. NLO phase retrieval relies on analytic gradients to achieve efficiency. We developed a new approach for calculating these gradients, based on the technique of "reverse-mode algorithmic differentiation" which allows gradients to be derived quickly and reduces the work of developing new phase retrieval models. We developed an algorithm for reconstructing pupil amplitude and phase from a single defocused image (previously three or more were needed) for hard-edged binary apertures. We developed Fourier transform models, based on the chirp z-transform (CZT), that allow flexible control of sampling in the pupil and image domains for phase retrieval algorithms. In some common cases, these models can be at least as fast as FFT-based algorithms. We used the CZT model to derive an algorithm for retrieving unknown sampling ratios (Q) jointly with wavefronts using an analytic gradient"--Pages ix-x.
Author: Matthais Thomas Banet
Author: Matthais Thomas Banet
Author: Robert L. Johnson
Author: Michael C. Roggemann
Author: 
Author: Robert K. Tyson
Author: 
Author: 
Author: Stanley H. Chan
Author: Lakhmi C. Jain
Author: Alden S. Jurling