Digital Image Computing
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Computer Imaging
Computer Imaging: Digital Image Analysis and Processing brings together analysis and processing in a unified framework, providing a valuable foundation for understanding both computer vision and image processing applications. Taking an engineering approach, the text integrates theory with a conceptual and application-oriented style, allowing you to immediately understand how each topic fits into the overall structure of practical application development. Divided into five major parts, the book begins by introducing the concepts and definitions necessary to understand computer imaging. The second part describes image analysis and provides the tools, concepts, and models required to analyze digital images and develop computer vision applications. Part III discusses application areas for the processing of images, emphasizing human visual perception. Part IV delivers the information required to apply a CVIPtools environment to algorithm development. The text concludes with appendices that provide supplemental imaging information and assist with the programming exercises found in each chapter. The author presents topics as needed for understanding each practical imaging model being studied. This motivates the reader to master the topics and also makes the book useful as a reference. The CVIPtools software integrated throughout the book, now in a new Windows version, provides practical examples and encourages you to conduct additional exploration via tutorials and programming exercises provided with each chapter.
Principles of Digital Image Processing
Author: Wilhelm Burger
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-07-08
This is the second volume of a book series that provides a modern, algori- mic introduction to digital image processing. It is designed to be used both by learners desiring a ?rm foundation on which to build and practitioners in search of critical analysis and modern implementations of the most important techniques. This updated and enhanced paperback edition of our compreh- sive textbook Digital Image Processing: An Algorithmic Approach Using Java packages the original material into a series of compact volumes, thereby s- porting a ?exible sequence of courses in digital image processing. Tailoring the contents to the scope of individual semester courses is also an attempt to p- vide a?ordable (and “backpack-compatible”) textbooks without comprimising the quality and depth of content. This second volume, titled Core Algorithms, extends the introductory - terial presented in the ?rst volume (Fundamental Techniques) with additional techniques that are, nevertheless, part of the standard image processing to- box. A forthcomingthird volume(Advanced Techniques) will extendthis series and add important material beyond the elementary level, suitable for an - vanced undergraduate or even graduate course.
Digital Image Processing Algorithms and Applications
A unique collection of algorithms and lab experiments for practitioners and researchers of digital image processing technology With the field of digital image processing rapidly expanding, there is a growing need for a book that would go beyond theory and techniques to address the underlying algorithms. Digital Image Processing Algorithms and Applications fills the gap in the field, providing scientists and engineers with a complete library of algorithms for digital image processing, coding, and analysis. Digital image transform algorithms, edge detection algorithms, and image segmentation algorithms are carefully gleaned from the literature for compatibility and a track record of acceptance in the scientific community. The author guides readers through all facets of the technology, supplementing the discussion with detailed lab exercises in EIKONA, his own digital image processing software, as well as useful PDF transparencies. He covers in depth filtering and enhancement, transforms, compression, edge detection, region segmentation, and shape analysis, explaining at every step the relevant theory, algorithm structure, and its use for problem solving in various applications. The availability of the lab exercises and the source code (all algorithms are presented in C-code) over the Internet makes the book an invaluable self-study guide. It also lets interested readers develop digital image processing applications on ordinary desktop computers as well as on Unix machines.