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.

Preface 1. Introduction 2. Image digitization 3. Digital image formation and computational imaging 4. Image resampling and building continuous image models 5. Image and noise statistical characterization and diagnostics 6. Statistical image models and pattern formation 7. Image correlators for detection and localization of objects 8. Methods of image perfecting 9. Methods of image enhancement

This book offers a unique combination of theory, exercises, supportive software and data set that can be used not only for studying the subject, but also in further practical work.The first edition of this textbook focussed on providing practical hands-on experience in digital imaging techniques. While the original concentrated on practical applications, it kept to a minimum any detailed discussion of the underlying theory. In this new extended, self-contained edition, the author builds on the strength of the first edition by expanding the coverage and including formulations and intuitive explanations of major theoretical results that underlie the exercises.Addressing 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 (denoizing, deblurring), methods of image enhancement and supplemented with more than 100 exercises in MATLAB® in all major topics of the subject, this text enables readers to master digital imaging on both fundamental theoretical and practical levels.MATLAB® source codes for the exercises are provided, which readers can modify for their particular needs and tastes, to design new exercises and, in addition, to use them for solving particular image-processing tasks.