With the ubiquitous use of digital imaging, a new profession has emerged: imaging engineering. Designed for newcomers to imaging science and engineering, Theoretical Foundations of Digital Imaging Using MATLAB® treats the theory of digital imaging as a specific branch of science. It covers the subject in its entirety, from image formation to image perfecting.
Based on the author’s 50 years of working and teaching in the field, the text first addresses the problem of converting images into digital signals that can be stored, transmitted, and processed on digital computers. It then explains how to adequately represent image transformations on computers. After presenting several examples of computational imaging, including numerical reconstruction of holograms and virtual image formation through computer-generated display holograms, the author introduces methods for image perfect resampling and building continuous image models. He also examines the fundamental problem of the optimal estimation of image parameters, such as how to localize targets in images. The book concludes with a comprehensive discussion of linear and nonlinear filtering methods for image perfecting and enhancement.
Helping you master digital imaging, this book presents a unified theoretical basis for understanding and designing methods of imaging and image processing. To facilitate a deeper understanding of the major results, it offers a number of exercises supported by MATLAB programs, with the code available at www.crcpress.com.
Table of Contents
Introduction. Mathematical Preliminaries. Image Digitization. Discrete Signal Transformations. Digital Image Formation and Computational Imaging. Image Resampling and Building Continuous Image Models. Image Parameter Estimation: Case Study—Localization of Objects in Images. Image Perfecting. Index.
Leonid P. Yaroslavsky is a professor emeritus at Tel Aviv University. A fellow of the Optical Society of America, Dr. Yaroslavsky has authored more than 100 papers on digital image processing and digital holography.
"This seminal and highly influential monograph focuses on concrete phenomena for understanding and designing methods of imaging and image processing. … The reader will find a careful discussion of computational imaging, standard material about image reconstruction from sparse sampled data, description of statistically optimal estimation of image numerical parameters, and a presentation of various exercises supported by MATLAB programs."
—Christian Brosseau, Optics & Photonics News
"this is an excellent in-depth review of the fundamentals of digital imaging, best read for its general foundational content" —Contemporary Physics (Aug 2016)
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