Image Representation And Processing
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Image Representation and Processing
Author: V.V. Alexandrov
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Recently, much attention has been paid to image processing with multiresolution and hierarchical structures such as pyramids and trees. This volume deals with recursive pyramids, which combine the advantages of available multiresolution structures and which are convenient both for global and local image processing. Recursive pyramids are based on regular hierarchical (recursive) structures containing data on image fragments of different sizes. Such an image representation technique enables the effective manipulation of pictorial information as well as the development of special hardware or data structures. The major aspects of this book are two original mathematical models of greyscale and binary images represented by recursive structures. Image compression, transmission and processing are discussed using these models. A number of applications are presented, including optical character recognition, expert systems and special computer architecture for pictorial data processing. The majority of results are presented as algorithms applicable to discrete information fields of arbitrary dimensions (e.g. 2-D or 3-D images). The book is divided into six chapters: Chapter 1 provides a brief introduction. Chapter 2 then deals with recursive structures and their properties. Chapter 3 introduces pyramidal image models. Image coding and the progressive transmission of images with gradual refinement are discussed in Chapter 4. Chapters 5 and 6 are devoted to image processing with pyramidal-recursive structures and applications. The volume concludes with a comprehensive bibliography. For applied mathematicians and computer scientists whose work involves computer vision, information theory and other aspects of image representation techniques.
Image Processing and Analysis
This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.
Image Processing and Pattern Recognition
A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.