Image Processing For Computer Graphics

The focus of this book is on providing a thorough treatment of image processing with an emphasis on those aspects most used in computer graphics. Throughout, the authors concentrate on describing and analysing the underlying concepts rather than on presenting algorithms or pseudocode. As befits a modern introduction to this topic, a healthy balance is struck between discussing the underlying mathematics of the subject and the main topics covered: signal processing, data discretization, the theory of colour and different colour systems, operations in images, dithering and half-toning, warping and morphing, and image processing.

Image processing is concerned with the analysis and manipulation of images by computer. Providing a thorough treatment of image processing with an emphasis on those aspects most used in computer graphics, the authors concentrate on describing and analyzing the underlying concepts rather than on presenting algorithms or pseudocode. As befits a modern introduction to this topic, a good balance is struck between discussing the underlying mathematics and the main topics: signal processing, data discretization, the theory of colour and different colour systems, operations in images, dithering and half-toning, warping and morphing and image processing. This second edition reflects recent trends in science andtechnology that exploit image processing in computer graphics and vision applications. Stochastic image models and statistical methods for image processing are covered as are: A modern approach and new developments in the area, Probability theory for image processing, Applications in image analysis and computer vision.

A cookbook of the hottest new algorithms and cutting-edge techniques in image processing and computer vision This amazing book/CD package puts the power of all the hottest new image processing techniques and algorithms in your hands. Based on J. R. Parker's exhaustive survey of Internet newsgroups worldwide, Algorithms for Image Processing and Computer Vision answers the most frequently asked questions with practical solutions. Parker uses dozens of real-life examples taken from fields such as robotics, space exploration, forensic analysis, cartography, and medical diagnostics, to clearly describe the latest techniques for morphing, advanced edge detection, wavelets, texture classification, image restoration, symbol recognition, and genetic algorithms, to name just a few. And, best of all, he implements each method covered in C and provides all the source code on the CD. For the first time, you're rescued from the hours of mind-numbing mathematical calculations it would ordinarily take to program these state-of-the-art image processing capabilities into software. At last, nonmathematicians get all the shortcuts they need for sophisticated image recognition and processing applications. On the CD-ROM you'll find: * Complete code for examples in the book * A gallery of images illustrating the results of advanced techniques * A free GNU compiler that lets you run source code on any platform * A system for restoring damaged or blurred images * A genetic algorithms package

Information Theory (IT) tools, widely used in many scientific fields such as engineering, physics, genetics, neuroscience, and many others, are also useful transversal tools in image processing. In this book, we present the basic concepts of IT and how they have been used in the image processing areas of registration, segmentation, video processing, and computational aesthetics. Some of the approaches presented, such as the application of mutual information to registration, are the state of the art in the field. All techniques presented in this book have been previously published in peer-reviewed conference proceedings or international journals. We have stressed here their common aspects, and presented them in an unified way, so to make clear to the reader which problems IT tools can help to solve, which specific tools to use, and how to apply them. The IT basics are presented so as to be self-contained in the book. The intended audiences are students and practitioners of image processing and related areas such as computer graphics and visualization. In addition, students and practitioners of IT will be interested in knowing about these applications.

Information Theory (IT) tools, widely used in many scientific fields such as engineering, physics, genetics, neuroscience, and many others, are also useful transversal tools in image processing. In this book, we present the basic concepts of IT and how they have been used in the image processing areas of registration, segmentation, video processing, and computational aesthetics. Some of the approaches presented, such as the application of mutual information to registration, are the state of the art in the field. All techniques presented in this book have been previously published in peer-reviewed conference proceedings or international journals. We have stressed here their common aspects, and presented them in an unified way, so to make clear to the reader which problems IT tools can help to solve, which specific tools to use, and how to apply them. The IT basics are presented so as to be self-contained in the book. The intended audiences are students and practitioners of image processing and related areas such as computer graphics and visualization. In addition, students and practitioners of IT will be interested in knowing about these applications. Table of Contents: Preface / Acknowledgments / Information Theory Basics / Image Registration / Image Segmentation / Video Key Frame Selection / Informational Aesthetics Measures / Bibliography / Authors' Biographies

Introduction to Visual Computing: Core Concepts in Computer Vision, Graphics, and Image Processing covers the fundamental concepts of visual computing. Whereas past books have treated these concepts within the context of specific fields such as computer graphics, computer vision or image processing, this book offers a unified view of these core concepts, thereby providing a unified treatment of computational and mathematical methods for creating, capturing, analyzing and manipulating visual data (e.g. 2D images, 3D models). Fundamentals covered in the book include convolution, Fourier transform, filters, geometric transformations, epipolar geometry, 3D reconstruction, color and the image synthesis pipeline. The book is organized in four parts. The first part provides an exposure to different kinds of visual data (e.g. 2D images, videos and 3D geometry) and the core mathematical techniques that are required for their processing (e.g. interpolation and linear regression.) The second part of the book on Image Based Visual Computing deals with several fundamental techniques to process 2D images (e.g. convolution, spectral analysis and feature detection) and corresponds to the low level retinal image processing that happens in the eye in the human visual system pathway. The next part of the book on Geometric Visual Computing deals with the fundamental techniques used to combine the geometric information from multiple eyes creating a 3D interpretation of the object and world around us (e.g. transformations, projective and epipolar geometry, and 3D reconstruction). This corresponds to the higher level processing that happens in the brain combining information from both the eyes thereby helping us to navigate through the 3D world around us. The last two parts of the book cover Radiometric Visual Computing and Visual Content Synthesis. These parts focus on the fundamental techniques for processing information arising from the interaction of light with objects around us, as well as the fundamentals of creating virtual computer generated worlds that mimic all the processing presented in the prior sections. The book is written for a 16 week long semester course and can be used for both undergraduate and graduate teaching, as well as a reference for professionals.

Computer Vision and Image Processing contains review papers from the Computer Vision, Graphics, and Image Processing volume covering a large variety of vision-related topics. Organized into five parts encompassing 26 chapters, the book covers topics on image-level operations and architectures; image representation and recognition; and three-dimensional imaging. The introductory part of this book is concerned with the end-to-end performance of image gathering and processing for high-resolution edge detection. It proposes methods using mathematical morphology to provide a complete edge detection process that may be used with any slope approximating operator. This part also discusses the automatic control of low-level robot vision, presents an image partitioning method suited for parallel implementation, and describes invariant architectures for low-level vision. The subsequent two sections present significant topics on image representation and recognition. Topics covered include the use of the primitives chain code; the geometric properties of the generalized cone; efficient rendering and structural-statistical character recognition algorithms; multi-level thresholding for image segmentation; knowledge-based object recognition system; and shape decomposition method based on perceptual structure. The fourth part describes a rule-based expert system for recovering three-dimensional shape and orientation. A procedure of intensity-guided range sensing to gain insights on the concept of cooperative-and-iterative strategy is also presented in this part. The concluding part contains supplementary texts on texture segmentation using topographic labels and an improved algorithm for labeling connected components in a binary image. Additional algorithms for three-dimensional motion parameter determination and surface tracking in three-dimensional binary images are also provided.

The technological developments of the last ten years have made com puter graphics and image processing by computer popular. Pictorial pat tern recognition has also shown significant progress. Clearly, there exist overlapping interests among the three areas of research. Graphic displays are of concern to anyone involved in image processing or pic torial pattern recognition and many problems in graphics require methodologies from image processing for their solutions. The data structures used in all three areas are similar. It seems that there is a common body of knowledge underlying all three areas, pictorial informa tion processing by computer. The novelty of these fields makes it difficult to design a course or to a write a book covering their basic concepts. Some of the treatises on graphics focus on the hardware and methods of current interest while treatises on image processing often emphasize applications and classical signal processing. The fast evolution of technology causes such material to lose its relevance. For example, the development of optical fibers has reduced the importance of bandwidth compression.