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.

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

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.

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

Whether obtained by microscopes, space probes, or the human eye, the same basic tools can be applied to acquire, process, and analyze the data contained in images. Ideal for self study, The Image Processing Handbook, Sixth Edition, first published in 1992, raises the bar once again as the gold-standard reference on this subject. Using extensive new illustrations and diagrams, it offers a logically organized exploration of the important relationship between 2D images and the 3D structures they reveal. Provides Hundreds of Visual Examples in FULL COLOR! The author focuses on helping readers visualize and compare processing and measurement operations and how they are typically combined in fields ranging from microscopy and astronomy to real-world scientific, industrial, and forensic applications. Presenting methods in the order in which they would be applied in a typical workflow—from acquisition to interpretation—this book compares a wide range of algorithms used to: Improve the appearance, printing, and transmission of an image Prepare images for measurement of the features and structures they reveal Isolate objects and structures, and measure their size, shape, color, and position Correct defects and deal with limitations in images Enhance visual content and interpretation of details This handbook avoids dense mathematics, instead using new practical examples that better convey essential principles of image processing. This approach is more useful to develop readers’ grasp of how and why to apply processing techniques and ultimately process the mathematical foundations behind them. Much more than just an arbitrary collection of algorithms, this is the rare book that goes beyond mere image improvement, presenting a wide range of powerful example images that illustrate techniques involved in color processing and enhancement. Applying his 50-year experience as a scientist, educator, and industrial consultant, John Russ offers the benefit of his image processing expertise for fields ranging from astronomy and biomedical research to food science and forensics. His valuable insights and guidance continue to make this handbook a must-have reference.

55% new material in the latest edition of this “must-have for students and practitioners of image & video processing! This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today’s explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader’s own potential applications About the Editor... Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994. * No other resource for image and video processing contains the same breadth of up-to-date coverage * Each chapter written by one or several of the top experts working in that area * Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various, image-intensive disciplines