Optical Compressive Imaging

Optical Compressive Imaging

Author: Adrian Stern

Publisher: CRC Press

ISBN: 9781315354279

Category: Mathematics

Page: 304

View: 904

This dedicated overview of optical compressive imaging addresses implementation aspects of the revolutionary theory of compressive sensing (CS) in the field of optical imaging and sensing. It overviews the technological opportunities and challenges involved in optical design and implementation, from basic theory to optical architectures and systems for compressive imaging in various spectral regimes, spectral and hyperspectral imaging, polarimetric sensing, three-dimensional imaging, super-resolution imaging, lens-free, on-chip microscopy, and phase sensing and retrieval. The reader will gain a complete introduction to theory, experiment, and practical use for reducing hardware, shortening image scanning time, and improving image resolution as well as other performance parameters. Optics practitioners and optical system designers, electrical and optical engineers, mathematicians, and signal processing professionals will all find the book a unique trove of information and practical guidance. Delivers the first book on compressed sensing dealing with system development for a wide variety of optical imaging and sensing applications. Covers the fundamentals of CS theory, including noise and algorithms, as well as basic design approaches for data acquisition in optics. Addresses the challenges of implementing compressed sensing theory in the context of different optical imaging designs, from 3D imaging to tomography and microscopy. Provides an essential resource for the design of new and improved devices with improved image quality and shorter acquisition times. Adrian Stern, PhD, is associate professor and head of the Electro-Optical Engineering Unit at Ben-Gurion University of the Negev, Israel. He is an elected Fellow of SPIE.

Optical Compressive Imaging

Optical Compressive Imaging

Author: Adrian Stern

Publisher: CRC Press

ISBN: 9781498708074

Category: Mathematics

Page: 304

View: 156

This dedicated overview of optical compressive imaging addresses implementation aspects of the revolutionary theory of compressive sensing (CS) in the field of optical imaging and sensing. It overviews the technological opportunities and challenges involved in optical design and implementation, from basic theory to optical architectures and systems for compressive imaging in various spectral regimes, spectral and hyperspectral imaging, polarimetric sensing, three-dimensional imaging, super-resolution imaging, lens-free, on-chip microscopy, and phase sensing and retrieval. The reader will gain a complete introduction to theory, experiment, and practical use for reducing hardware, shortening image scanning time, and improving image resolution as well as other performance parameters. Optics practitioners and optical system designers, electrical and optical engineers, mathematicians, and signal processing professionals will all find the book a unique trove of information and practical guidance. Delivers the first book on compressed sensing dealing with system development for a wide variety of optical imaging and sensing applications. Covers the fundamentals of CS theory, including noise and algorithms, as well as basic design approaches for data acquisition in optics. Addresses the challenges of implementing compressed sensing theory in the context of different optical imaging designs, from 3D imaging to tomography and microscopy. Provides an essential resource for the design of new and improved devices with improved image quality and shorter acquisition times. Adrian Stern, PhD, is associate professor and head of the Electro-Optical Engineering Unit at Ben-Gurion University of the Negev, Israel. He is an elected Fellow of SPIE.

Optical Compressive Imaging

Optical Compressive Imaging

Author: Russell Duffy

Publisher: Createspace Independent Publishing Platform

ISBN: 1548309885

Category:

Page: 306

View: 225

An exciting new development has taken place in the digital era that has captured the imagination and talent of researchers around the globe - wavelet image compression. This technology has deep roots in theories of vision, and promises performance improvements over all other compression methods, such as those based on Fourier transforms, vectors quantizers, fractals, neural nets, and many others.

Compressive Imaging: Structure, Sampling, Learning

Compressive Imaging: Structure, Sampling, Learning

Author: Ben Adcock

Publisher: Cambridge University Press

ISBN: 9781108383912

Category: Computers

Page:

View: 395

Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging – including compressed sensing, wavelets and optimization – in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the pitfalls of these latest approaches.

Secure Compressive Sensing in Multimedia Data, Cloud Computing and IoT

Secure Compressive Sensing in Multimedia Data, Cloud Computing and IoT

Author: Yushu Zhang

Publisher: Springer

ISBN: 9789811325236

Category: Technology & Engineering

Page: 115

View: 892

This book gives a comprehensive and systematic review of secure compressive sensing (CS) for applications in various fields such as image processing, pattern recognition, Internet of things (IoT), and cloud computing. It will help readers grasp the knowledge of secure CS and its applications, and stimulate more readers to work on the research and development of secure CS. It discusses how CS becomes a cryptosystem, followed by the corresponding designs and analyses. The application of CS in multimedia data encryption is presented, in which the general design framework is given together with several particular frameworks including parallel CS, involvement of image processing techniques, and double protection mechanism. It also describes the applications of CS in cloud computing security and IoT security, i.e., privacy-preserving reconstruction in cloud computing and secure low-cost sampling in IoT, respectively.

Optical and Digital Image Processing

Optical and Digital Image Processing

Author: Gabriel Cristobal

Publisher: John Wiley & Sons

ISBN: 9783527635252

Category: Technology & Engineering

Page: 988

View: 874

In recent years, Moore's law has fostered the steady growth of the field of digital image processing, though the computational complexity remains a problem for most of the digital image processing applications. In parallel, the research domain of optical image processing has matured, potentially bypassing the problems digital approaches were suffering and bringing new applications. The advancement of technology calls for applications and knowledge at the intersection of both areas but there is a clear knowledge gap between the digital signal processing and the optical processing communities. This book covers the fundamental basis of the optical and image processing techniques by integrating contributions from both optical and digital research communities to solve current application bottlenecks, and give rise to new applications and solutions. Besides focusing on joint research, it also aims at disseminating the knowledge existing in both domains. Applications covered include image restoration, medical imaging, surveillance, holography, etc... "a very good book that deserves to be on the bookshelf of a serious student or scientist working in these areas." Source: Optics and Photonics News

3rd International Symposium of Space Optical Instruments and Applications

3rd International Symposium of Space Optical Instruments and Applications

Author: H. Paul Urbach

Publisher: Springer

ISBN: 9783319491844

Category: Science

Page: 517

View: 257

This volume contains selected and expanded contributions presented at the 3rd Symposium on Space Optical Instruments and Applications in Beijing, China June 28 – 29, 2016. This conference series is organised by the Sino-Holland Space Optical Instruments Laboratory, a cooperation platform between China and the Netherlands. The symposium focused on key technological problems of optical instruments and their applications in a space context. It covered the latest developments, experiments and results regarding theory, instrumentation and applications in space optics. The book is split across five topical sections. The first section covers space optical remote sensing system design, the second advanced optical system design, the third remote sensor calibration and measurement. Remote sensing data processing and information extraction is then presented, followed by a final section on remote sensing data applications.

Optical Supercomputing

Optical Supercomputing

Author: Shlomi Dolev

Publisher: Springer

ISBN: 9783642224942

Category: Computers

Page: 131

View: 734

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Optical SuperComputing, OSC 2010, held in Bertinoro, Italy, in November 2010. The 13 papers presented were carefully reviewed and selected for inclusion in this book. Being an annual forum for research presentations on all facets of optical computing for solving hard computation tasks, OCS addresses the following topics of interest: designs or demonstrations of optical computing devices, algorithmics and complexity issues of optical computing, computation representation by photons and holograms, neural and brain inspired architectures, electro-optic devices for interacting with optical computing devices, practical implementations, analysis of existing devices and case studies, optical photonics and laser switching technologies, optical and photonic memories, optical signal processing subsystems, optical networks for high-performance computing, optical interconnections, quantum optical systems, applications and algorithms for optical devices, Alpha particles, X-rays, and nano-technologies for optical computing.

Compressed Sensing and Its Applications

Compressed Sensing and Its Applications

Author: Holger Boche

Publisher: Birkhäuser

ISBN: 9783319730745

Category: Mathematics

Page: 295

View: 952

The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.

The Future of Hyperspectral Imaging

The Future of Hyperspectral Imaging

Author: Stefano Selci

Publisher: MDPI

ISBN: 9783039218226

Category: Science

Page: 220

View: 481

This book includes some very recent applications and the newest emerging trends of hyper-spectral imaging (HSI). HSI is a very recent and strange beast, a sort of a melting pot of previous techniques and scientific interests, merging and concentrating the efforts of physicists, chemists, botanists, biologists, and physicians, to mention just a few, as well as experts in data crunching and statistical elaboration. For almost a century, scientific observation, from looking to planets and stars down to our own cells and below, could be divided into two main categories: analyzing objects on the basis of their physical dimension (recording size, position, weight, etc. and their variations) or on how the object emits, reflects, or absorbs part of the electromagnetic spectrum, i.e., spectroscopy. While the two aspects have been obviously entangled, instruments and skills have always been clearly distinct from each other. With HSI now available, this is no longer the case. This instrument can return specimen dimensionalities and spectroscopic properties to any single pixel of your specimen, in a single set of data. HSI modality is ubiquitous and scale-invariant enough to be used to mark terrestrial resources on the basis of a land map obtained from satellite observation (actually, the oldest application of this type) or to understand if the cell you are looking at is cancerous or perfectly healthy. For all these reasons, HSI represents one of the most exciting methodologies of the new millennium.

Compressed Sensing with Side Information on the Feasible Region

Compressed Sensing with Side Information on the Feasible Region

Author: Mohammad Rostami

Publisher: Springer

ISBN: 9783319003665

Category: Computers

Page: 69

View: 351

This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.