Kirjahaku

An essential reference for optical sensor system design This is the first text to present an integrated view of the optical and mathematical analysis tools necessary to understand computational optical system design. It presents the foundations of computational optical sensor design with a focus entirely on digital imaging and spectroscopy. It systematically covers: Coded aperture and tomographic imaging Sampling and transformations in optical systems, including wavelets and generalized sampling techniques essential to digital system analysis Geometric, wave, and statistical models of optical fields The basic function of modern optical detectors and focal plane arrays Practical strategies for coherence measurement in imaging system design The sampling theory of digital imaging and spectroscopy for both conventional and emerging compressive and generalized measurement strategies Measurement code design Linear and nonlinear signal estimation The book concludes with a review of numerous design strategies in spectroscopy and imaging and clearly outlines the benefits and limits of each approach, including coded aperture and imaging spectroscopy, resonant and filter-based systems, and integrated design strategies to improve image resolution, depth of field, and field of view. Optical Imaging and Spectroscopy is an indispensable textbook for advanced undergraduate and graduate courses in optical sensor design. In addition to its direct applicability to optical system design, unique perspectives on computational sensor design presented in the text will be of interest for sensor designers in radio and millimeter wave, X-ray, and acoustic systems.

Computational optical imaging uses electromagnetic signals in the infrared, visible, ultraviolet, and x-ray wavelength ranges to characterize remote objects. This text explains how to create mathematical forward models describing tomographic, holographic, ptychographic, and photographic imaging systems. It describes image estimation algorithms, including those that use artificial neural networks and nonlinear estimators, to estimate still, video, and spectral images from measured data. The text considers geometric, diffractive, and statistical optical radiation models. It shows that advanced sensing and estimation strategies allow optical imagers to resolve targets with resolution exceeding conventional limits. It also considers how to maximize measurement efficiency and imager capacity using coded and feature-specific sampling and physical system design. Details not found in previous textbooks include coding strategies for compressive tomography, phase curvature in coherent imaging systems, the coherence transfer function, and interferometric focal planes. The last part of the book discusses digital camera design, including sampling optimization for photographic and video imaging and array camera design. This book focuses particularly on deep physical modeling of optical systems and algorithms. It aims to fill the gap between detector design and high-level image processing and to give readers the tools to design end-to-end imaging systems.