October 26, 2016
by CRC Press
Reference - 304 Pages - 57 Color & 80 B/W Illustrations
ISBN 9781498708067 - CAT# K24921
For Librarians Available on CRCnetBASE >>
Addresses the challenges of implementing compressed sensing theory in the context of different optical imaging designs, from 3D imaging to tomography and microscopy.
Covers the fundamentals of compressive sensing (CS) theory, including noise and algorithms, as well as basic design approaches for data acquisition in optics, and key challenges to practical implementation.
Enables readers to understand the use of different methods, important issues related to their use, and relevant limitations.
Provides an essential resource for the design of new acquisition devices such as light-field cameras and improvement of existing ones, such as in digital photography, for improved image quality and shorter acquisition times.
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.
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.
I. The theory of compressive sensing and its applications in optics. Introduction to compressive sensing theory. Compressive sensing theory for optical systems described by a continuous model. Multi-channel data acquisition optics design for compressive sensing. Special challenges in application of CS for optical imaging and sensing II. Compressive imaging systems. Optical architectures for compressive imaging. Terahertz imaging with compressed sensing. Infrared imaging with compressed sensing. Motion compressive sensing. III. Compressive holography and compressive 3D imaging. Compressive holography. Performance analysis of Compressive Holography. Incoherent Compressive Holography. Compressive Integral Imaging. Compressive light-field sensing. IV. Spectral, hyperspectral imaging, and polarimetric compressive sensing systems. Compressive coded aperture spectral imaging. Compressive spectral and hyperspectral sensing with layered devices. Compressive polarimetric sensing. V. Seeing fine details with compressive sensing: microscopy and super-resolution. Super-resolution of sparse images using coherent and incoherent light. Compressive fluorescents microscopy. STORM using compressed sensing. CS methods for lens-free, on-chip microscopy. VI. Phase sensing, phase retrieval and phase tomography. Phase space tomography . Phase retrieval of sparse images.
"This is the book on how to bypass the sampling constraints of modern imaging systems. From a mathematical point of view, it deals with the problem of extracting information from an underdetermined system of equations. It is wide in its scope, covering applications ranging from holography and microscopy, to hyperspectral or polarization imaging. Readers can easily find out what can be done with this kind of imaging…."
–Optics & Photonics News (May 2017)