Leonid P. Yaroslavsky – författare

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.

In this book, Prof. Yaroslavsky delivers a complete applied course in digital imaging aimed at advanced students and practitioners. Covering all areas of digital imaging, the text provides an outline of underlying principles of each topic before offering more than 80 MATLAB® based exercises. Subjects addressed embrace image digitization (discretization, quantization, compression), digital image formation and computational imaging, image resampling and building continuous image models, image and noise statistical characterization and diagnostics, statistical image models and pattern formation, image correlators for localization of objects, methods of image perfecting (denoising, deblurring), and methods of image enhancement.

The first edition of this text book focussed on providing practical hands-on experience in digital imaging techniques for graduate students and practitioners keeping to a minimum any detailed discussion on the underlying theory. In this new extended edition, the author builds on the strength of the original edition by expanding the coverage to include formulation of the major theoretical results that underlie the exercises as well as introducing numerous modern concepts and new techniques. Whether you are studying or already using digital imaging techniques, developing proficiency in the subject is not possible without mastering practical skills. Including more than 100 MATLAB® exercises, this book delivers a complete applied course in digital imaging theory and practice.

Helping readers master digital imaging, this text presents a unified theoretical basis for understanding and designing methods of imaging and image processing. Designed for newcomers to imaging science and engineering, the book covers the subject in its entirety, from image formation to image perfecting. The author avoids using heavy mathematics and derives all formulas in full detail. To facilitate a deeper understanding of the major results, the book includes a number of exercises supported by MATLAB programs.

Helping readers master digital imaging, this text presents a unified theoretical basis for understanding and designing methods of imaging and image processing. Designed for newcomers to imaging science and engineering, the book covers the subject in its entirety, from image formation to image perfecting. The author avoids using heavy mathematics and derives all formulas in full detail. To facilitate a deeper understanding of the major results, the book includes a number of exercises supported by MATLAB programs.

This book provides both the most updated formulations of the sampling theory and practical algorithms of image sampling with sampling rates close to the theoretical minimum, as well interpolation-error-free methods of image resampling and the theory of discrete representation of signal integral transforms. Topics include classical sampling theory, compressed sensing, non-redundant sampling, fast signal resampling algorithms, the discrete uncertainty principle, digital convolution, and various versions of discrete Fourier transforms. Exercises based in MATLAB supplement the text throughout.

The text has been prepared for researchers involved in picture processing. It is designed to help them in mastering the methods at the professional level. From the viewpoint of both signal theory and information theory, the treatment covers the basic principles of the digital methods for the processing of continuous signals such as picture signals. In addition, it reviews schemes for correcting signal distortion in imaging systems, for the enhancement of picture contrast, and for the automatic measurement of picture details. The text contains new results on digital filtering and transformation, and a new approach to picture processing. The main applications, as documented by numerous examples, are in space research, remote sensing, medical diag­ nostics, nondestructive testing. The material has been tested extensively in class-room use with students of both computer science and electrical engineering at the senior undergraduate and the first-year graduate level. The present edition is not a translation of the original Russian book, but it has been extended substantially as well as updated. The author is grate­ ful to Dr. H. Lotsch of Springer-Verlag for his proposal to prepare this text and for many helpful suggestions. He likes to thank Dr. P. Hawkes for a careful copy-editing of the manuscript, and acknowledges numerous criti­ cal comments by Professors S.L. Gorelik, T.S. Huang, A.W. Lohmann,and A.M. Trakhtman.

The text has been prepared for researchers involved in picture processing. It is designed to help them in mastering the methods at the professional level. From the viewpoint of both signal theory and information theory, the treatment covers the basic principles of the digital methods for the processing of continuous signals such as picture signals. In addition, it reviews schemes for correcting signal distortion in imaging systems, for the enhancement of picture contrast, and for the automatic measurement of picture details. The text contains new results on digital filtering and transformation, and a new approach to picture processing. The main applications, as documented by numerous examples, are in space research, remote sensing, medical diag­ nostics, nondestructive testing. The material has been tested extensively in class-room use with students of both computer science and electrical engineering at the senior undergraduate and the first-year graduate level. The present edition is not a translation of the original Russian book, but it has been extended substantially as well as updated. The author is grate­ ful to Dr. H. Lotsch of Springer-Verlag for his proposal to prepare this text and for many helpful suggestions. He likes to thank Dr. P. Hawkes for a careful copy-editing of the manuscript, and acknowledges numerous criti­ cal comments by Professors S.L. Gorelik, T.S. Huang, A.W. Lohmann,and A.M. Trakhtman.