Handbook of Image Processing Operators Reinhard Klette Berlin Technical University, Germany Piero Zamperoni Braunschweig Technical University, Germany The practical applications of digital image processing have expanded significantly in recent years. Interest is increasing over a wide range of disciplines, from computer vision to biomedical imaging and mechanical inspection. An invaluable reference source for all who work in image processing, this text describes the complete range of standard image processing operators and transformations. Coverage spans the fundamentals of image processing, introducing the basic terminology, describing the general control structures and illustrating a range of algorithmical procedures. The major strength of this book lies in its practical approach, offering the user operative solutions to a broad range of specific application problems in image analysis, image enhancement and feature extraction. To this end it serves as a reference to select the most suitable operators for any given problem. After the introductory chapters, each operator is presented in the same form: characterization, mathematical definition, comments and algorithmic aspects, pseudo-program, and bibliographic references. An indispensable guide for computer applications engineers at a professional, academic or research level in communications, natural sciences, medicine, and robotics who have to solve field-specific application problems using advanced digital image processing techniques. The source codes for all the operators described in the text are available on disk for UNIX and MS-DOS systems, see inside for details.

Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously. Volume 1 (From Energy to Image) examines the formation, properties, and enhancement of a digital image. Topics and features: • Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy • Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal • Discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image • Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration • Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest • Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration • Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence. Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.

Now in its fifth edition, John C. Russ‘s monumental image processing reference is an even more complete, modern, and hands-on tool than ever before. The Image Processing Handbook, Fifth Edition is fully updated and expanded to reflect the latest developments in the field. Written by an expert with unequalled experience and authority, it offers clea

Image techniques have been developed and implemented for various purposes, and image engineering (IE) is a rapidly evolving, integrated discipline comprising the study of all the different branches of image techniques, and encompassing mathematics, physics, biology, physiology, psychology, electrical engineering, computer science and automation. Advances in the field are also closely related to the development of telecommunications, biomedical engineering, remote sensing, surveying and mapping, as well as document processing and industrial applications. IE involves three related and partially overlapping groups of image techniques: image processing (IP) (in its narrow sense), image analysis (IA) and image understanding (IU), and the integration of these three groups makes the discipline of image engineering an important part of the modern information era. This is the first handbook on image engineering, and provides a well-structured, comprehensive overview of this new discipline. It also offers detailed information on the various image techniques. It is a valuable reference resource for R&D professional and undergraduate students involved in image-related activities.

For decades, researchers have been developing algorithms to manipulate and analyze images. From this, a common set of image tools now appear in many high-level programming languages. Consequently, the amount of coding required by a user has significantly lessened over the years. While the libraries for image analysis are coalescing to a common toolkit, the language of image analysis has remained stagnant. Often, textual descriptions of an analytical protocol consume far more real estate than does the computer code required to execute the processes. Furthermore, the textual explanations are sometimes vague or incomplete. This book offers a precise mathematical language for the field of image processing. Defined operators correspond directly to standard library routines, greatly facilitating the translation between mathematical descriptions and computer script. This text is presented with Python 3 examples. This text will provide a unified language for image processing Provides the theoretical foundations with accompanied Python® scripts to precisely describe steps in image processing applications Linkage between scripts and theory through operators will be presented All chapters will contain theories, operator equivalents, examples, Python® codes, and exercises

Consistently rated as the best overall introduction to computer-based image processing, The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more. Incorporating image processing and analysis examples at all scales, from nano- to astro-, this Seventh Edition: Features a greater range of computationally intensive algorithms than previous versions Provides better organization, more quantitative results, and new material on recent developments Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines Presents 500+ entirely new figures and images, with more than two-thirds appearing in color The Image Processing Handbook, Seventh Edition delivers an accessible and up-to-date treatment of image processing, offering broad coverage and comparison of algorithms, approaches, and outcomes.

Image processing is fast becoming a valuable tool for analyzing multidimensional data in all areas of natural science. Since the publication of the best-selling first edition of this handbook, the field of image processing has matured in many of its aspects from ad hoc, empirical approaches to a sound science based on established mathematical and p