Computational Imaging
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Computational Photography
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Author : Rastislav Lukac
language : en
Publisher: CRC Press
Release Date : 2017-12-19
Computational Photography written by Rastislav Lukac and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Computers categories.
Computational photography refers broadly to imaging techniques that enhance or extend the capabilities of digital photography. This new and rapidly developing research field has evolved from computer vision, image processing, computer graphics and applied optics—and numerous commercial products capitalizing on its principles have already appeared in diverse market applications, due to the gradual migration of computational algorithms from computers to imaging devices and software. Computational Photography: Methods and Applications provides a strong, fundamental understanding of theory and methods, and a foundation upon which to build solutions for many of today's most interesting and challenging computational imaging problems. Elucidating cutting-edge advances and applications in digital imaging, camera image processing, and computational photography, with a focus on related research challenges, this book: Describes single capture image fusion technology for consumer digital cameras Discusses the steps in a camera image processing pipeline, such as visual data compression, color correction and enhancement, denoising, demosaicking, super-resolution reconstruction, deblurring, and high dynamic range imaging Covers shadow detection for surveillance applications, camera-driven document rectification, bilateral filtering and its applications, and painterly rendering of digital images Presents machine-learning methods for automatic image colorization and digital face beautification Explores light field acquisition and processing, space-time light field rendering, and dynamic view synthesis with an array of cameras Because of the urgent challenges associated with emerging digital camera applications, image processing methods for computational photography are of paramount importance to research and development in the imaging community. Presenting the work of leading experts, and edited by a renowned authority in digital color imaging and camera image processing, this book considers the rapid developments in this area and addresses very particular research and application problems. It is ideal as a stand-alone professional reference for design and implementation of digital image and video processing tasks, and it can also be used to support graduate courses in computer vision, digital imaging, visual data processing, and computer graphics, among others.
Computational Imaging
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Author : Ayush Bhandari
language : en
Publisher: MIT Press
Release Date : 2022-10-25
Computational Imaging written by Ayush Bhandari and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-25 with Technology & Engineering categories.
A comprehensive and up-to-date textbook and reference for computational imaging, which combines vision, graphics, signal processing, and optics. Computational imaging involves the joint design of imaging hardware and computer algorithms to create novel imaging systems with unprecedented capabilities. In recent years such capabilities include cameras that operate at a trillion frames per second, microscopes that can see small viruses long thought to be optically irresolvable, and telescopes that capture images of black holes. This text offers a comprehensive and up-to-date introduction to this rapidly growing field, a convergence of vision, graphics, signal processing, and optics. It can be used as an instructional resource for computer imaging courses and as a reference for professionals. It covers the fundamentals of the field, current research and applications, and light transport techniques. The text first presents an imaging toolkit, including optics, image sensors, and illumination, and a computational toolkit, introducing modeling, mathematical tools, model-based inversion, data-driven inversion techniques, and hybrid inversion techniques. It then examines different modalities of light, focusing on the plenoptic function, which describes degrees of freedom of a light ray. Finally, the text outlines light transport techniques, describing imaging systems that obtain micron-scale 3D shape or optimize for noise-free imaging, optical computing, and non-line-of-sight imaging. Throughout, it discusses the use of computational imaging methods in a range of application areas, including smart phone photography, autonomous driving, and medical imaging. End-of-chapter exercises help put the material in context.
Deep Learning For Computational Imaging
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Author : Reinhard Heckel
language : en
Publisher: Oxford University Press
Release Date : 2025-04-30
Deep Learning For Computational Imaging written by Reinhard Heckel and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-30 with Mathematics categories.
Computational techniques for image reconstruction problems enable imaging technologies including high-resolution microscopy, astronomy and seismology, computed tomography, and magnetic resonance imaging. Until recently, methods for solving such inverse problems were derived by experts without any learning. Now, the best performing image reconstruction methods are based on deep learning. This textbook gives the first comprehensive introduction to deep learning based image reconstruction methods. This book first introduces important inverse problems in imaging, including denoising and reconstructing an image from few and noisy measurements, and explains what makes those problems hard and interesting. Then, the book briefly discusses traditional optimization and sparsity based reconstruction methods, as well as optimization techniques as a basis for training and deriving deep neural networks for image reconstruction. The main part of the book is about how to solve image reconstruction problems with deep learning techniques: The book first disuses supervised deep learning approaches that map a measurement to an image as well as network architectures for imaging including convolutional neural networks and transformers. Then, reconstruction approaches based on generative models such as variational autoencoders and diffusion models are discussed, and how un-trained neural networks and implicit neural representations enable signal and image reconstruction. The book ends with a discussion on the robustness of deep learning based reconstruction as well as a discussion on the important topic of evaluating models and datasets, which are a critical ingredient of deep learning based imaging.
Foundations Of Computational Imaging
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Author : Charles A. Bouman
language : en
Publisher: SIAM
Release Date : 2022-07-06
Foundations Of Computational Imaging written by Charles A. Bouman and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-06 with Mathematics categories.
Collecting a set of classical and emerging methods previously unavailable in a single resource, Foundations of Computational Imaging: A Model-Based Approach is the first book to define a common foundation for the mathematical and statistical methods used in computational imaging. The book brings together a blend of research with applications in a variety of disciplines, including applied math, physics, chemistry, optics, and signal processing, to address a collection of problems that can benefit from a common set of methods. Readers will find basic techniques of model-based image processing, a comprehensive treatment of Bayesian and regularized image reconstruction methods, and an integrated treatment of advanced reconstruction techniques, such as majorization, constrained optimization, alternating direction method of multipliers (ADMM), and Plug-and-Play methods for model integration. Foundations of Computational Imaging can be used in courses on model-based or computational imaging, advanced numerical analysis, data science, numerical optimization, and approximation theory. It will also prove useful to researchers or practitioners in medical, scientific, commercial, and industrial imaging.
Computational Imaging And Analytics In Biomedical Engineering
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Author : T. R. Ganesh Babu
language : en
Publisher: CRC Press
Release Date : 2024-07-26
Computational Imaging And Analytics In Biomedical Engineering written by T. R. Ganesh Babu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-26 with Computers categories.
This new book focuses on mathematical and numerical methods for medical images and data. The book presents the various mathematical modeling techniques, numerical analysis, computing and computational techniques, and applications of machine learning for medical images and medical informatics. It also focuses on programming concepts using MATLAB and Phython for medical image and signal analytics. The volume demonstrates the use of computational techniques and tools such as machine learning, deep neural networks, artificial intelligence and human-computer interaction ,fusion methods for CT and pet images, etc., for diagnosis of brain disorders, cervical cancer, lung disease, melanoma, atrial fibrillation and other circulatory issues, dental images, diabetes, and other medical issues.
Computational Photography
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Author : Saghi Hajisharif
language : en
Publisher: Linköping University Electronic Press
Release Date : 2020-02-18
Computational Photography written by Saghi Hajisharif and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-18 with categories.
The introduction and recent advancements of computational photography have revolutionized the imaging industry. Computational photography is a combination of imaging techniques at the intersection of various fields such as optics, computer vision, and computer graphics. These methods enhance the capabilities of traditional digital photography by applying computational techniques both during and after the capturing process. This thesis targets two major subjects in this field: High Dynamic Range (HDR) image reconstruction and Light Field (LF) compressive capturing, compression, and real-time rendering. The first part of the thesis focuses on the HDR images that concurrently contain detailed information from the very dark shadows to the brightest areas in the scenes. One of the main contributions presented in this thesis is the development of a unified reconstruction algorithm for spatially variant exposures in a single image. This method is based on a camera noise model, and it simultaneously resamples, reconstructs, denoises, and demosaics the image while extending its dynamic range. Furthermore, the HDR reconstruction algorithm is extended to adapt to the local features of the image, as well as the noise statistics, to preserve the high-frequency edges during reconstruction. In the second part of this thesis, the research focus shifts to the acquisition, encoding, reconstruction, and rendering of light field images and videos in a real-time setting. Unlike traditional integral photography, a light field captures the information of the dynamic environment from all angles, all points in space, and all spectral wavelength and time. This thesis employs sparse representation to provide an end-to-end solution to the problem of encoding, real-time reconstruction, and rendering of high dimensional light field video data sets. These solutions are applied on various types of data sets, such as light fields captured with multi-camera systems or hand-held cameras equipped with micro-lens arrays, and spherical light fields. Finally, sparse representation of light fields was utilized for developing a single sensor light field video camera equipped with a color-coded mask. A new compressive sensing model is presented that is suitable for dynamic scenes with temporal coherency and is capable of reconstructing high-resolution light field videos.
Computational Imaging
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Author :
language : en
Publisher:
Release Date : 2006
Computational Imaging written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Image processing categories.
Computational Optical Imaging
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Author : Zhengjun Liu
language : en
Publisher: Springer
Release Date : 2025-05-11
Computational Optical Imaging written by Zhengjun Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-11 with Science categories.
This book highlights a comprehensive introduction to the principles and calculation methods of computational optical imaging. Integrating optical imaging and computing technology to achieve significant performance improvements, computational optical imaging has become an active research field in optics. It has given rise to the emerging of new concepts such as computational imaging, computational measurement and computational photography. As high-performance image detectors make image measurements discrete and digital, images are mostly recorded in the form of discrete data, almost replacing the continuous medium used for pattern recording. Computational optical imaging technology has become an effective way for people to study microscopic imaging. At present, different imaging systems are composed of continuous optical elements such as lenses and prisms or discrete optical elements such as spatial light modulators or digital micro-mirror devices. The current computing technology has permeated all aspects of imaging systems and gradually promotes the digitization of optical imaging systems. This book summarizes the representative work done in this field and introduces the latest results. Computing technology plays an important bridging role between theories of optics and experimental systems, which inspires more comprehensive and in-depth research. It has the advantages of high repeatability, flexibility, strong computing power and low cost. In this multidisciplinary field, researchers in computer science, optics and information science have joined together to extend its depth and breadth. Targeting cutting-edge issues to be solved in computational optics, this book introduces a variety of methods that involve theoretical innovations and technical breakthroughs in imaging resolution, the field of view, imaging speed, and computing speed. It intends to provide a handy reference and technical support for graduate students, researchers and professionals engaged in the study and practice of computational optical imaging.
Integrated Computational Imaging Systems
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Author : Joseph Van der Gracht
language : en
Publisher:
Release Date : 2002
Integrated Computational Imaging Systems written by Joseph Van der Gracht and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Technology & Engineering categories.
Digest and expanded papers from a November 2001 meeting offer definitions of integrated imaging, present examples of imaging systems, and describe concepts from information theory as they apply to the analysis and design of imaging systems. Material is in sections on key topics, wavefront coding, computational microscopes, information theory and design, imaging systems, implementation, hyperspectral systems, and analysis and situation. Three-dimensional coherence imaging in the Fresnel domain, spatial tomography and coherence microscopy, and modeling of sparse aperture telescope image quality are some of the areas discussed. Annotation copyrighted by Book News, Inc., Portland, OR
Fourier Optics And Computational Imaging
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Author : Kedar Khare
language : en
Publisher: John Wiley & Sons
Release Date : 2015-09-21
Fourier Optics And Computational Imaging written by Kedar Khare and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-21 with Technology & Engineering categories.
This book covers both the mathematics of inverse problems and optical systems design, and includes a review of the mathematical methods and Fourier optics. The first part of the book deals with the mathematical tools in detail with minimal assumption about prior knowledge on the part of the reader. The second part of the book discusses concepts in optics, particularly propagation of optical waves and coherence properties of optical fields that form the basis of the computational models used for image recovery. The third part provides a discussion of specific imaging systems that illustrate the power of the hybrid computational imaging model in enhancing imaging performance. A number of exercises are provided for readers to develop further understanding of computational imaging. While the focus of the book is largely on optical imaging systems, the key concepts are discussed in a fairly general manner so as to provide useful background for understanding the mechanisms of a diverse range of imaging modalities.