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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.
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.
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.
This hands-on book thoroughly covers the nature of turbulence effects on optical imaging systems, techniques used to overcome these effects, performance analysis methods, and representative examples on 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.
Speckle imaging techniques make it possible to do high-resolution imaging through the turbulent atmosphere by collecting and processing a large number of short-exposure frames, each of which effectively freezes the atmosphere. In severe seeing condition, when the characteristic scale of atmospheric fluctuations is much smaller than the diameter of the telescope, the reconstructed image is dominated by?turbulence noise? caused by redundant baselines in the pupil. I describe a generalization of aperture masking interferometery that dramatically improves imaging performance in this regime. The approach is to partition the aperture into annuli, form the bispectra of the focal plane images formed from each annulus, and recombine them into a synthesized bispectrum form which the object may be retrieved. This may be implemented using multiple cameras and special mirrors, or with a single camera and a suitable pupil phase mask. I report results from simulations as well as experimental results using telescopes at the Air Force Research Lab's Maui Space Surveillance Site.
The angular resolution of an imaging system is ultimately limited by diffraction effects related to the size of the image pupil once imperfections such as aberrations in the optical surfaces, grainy film, and noisy electronics have been eliminated. However, because of scatterings by turbulence, aerosols, and other inhomogeneities, the atmosphere diminishes the spatial coherence of propagating radiation and reduces the achievable resolution. Improving our ability to see through the atmosphere is of unmeasurable usefulness in astronomy, satellite imaging, remote detection, and all other areas in which high-resolution is desirable.