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Pyramid Algorithms presents a unique approach to understanding, analyzing, and computing the most common polynomial and spline curve and surface schemes used in computer-aided geometric design, employing a dynamic programming method based on recursive pyramids. The recursive pyramid approach offers the distinct advantage of revealing the entire structure of algorithms, as well as relationships between them, at a glance. This book-the only one built around this approach-is certain to change the way you think about CAGD and the way you perform it, and all it requires is a basic background in calculus and linear algebra, and simple programming skills.* Written by one of the world's most eminent CAGD researchers* Designed for use as both a professional reference and a textbook, and addressed to computer scientists, engineers, mathematicians, theoreticians, and students alike* Includes chapters on Bezier curves and surfaces, B-splines, blossoming, and multi-sided Bezier patches* Relies on an easily understood notation, and concludes each section with both practical and theoretical exercises that enhance and elaborate upon the discussion in the text* Foreword by Professor Helmut Pottmann, Vienna University of Technology
Parallel-Algorithms for Regular Architectures is the first book to concentrate exclusively on algorithms and paradigms for programming parallel computers such as the hypercube, mesh, pyramid, and mesh-of-trees.
This book constitutes the refereed proceedings of the 6th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007, held in Alicante, Spain in June 2007. It covers matching, distances and measures, graph-based segmentation and image processing, graph-based clustering, graph representations, pyramids, combinatorial maps and homologies, as well as graph clustering, embedding and learning.
This book contains the proceedings of the NATO Advanced Research Workshop held in Maratea (Italy), May 5-9, 1986 on Pyramidal Systems for Image Processing and Computer Vision. We had 40 participants from 11 countries playing an active part in the workshop and all the leaders of groups that have produced a prototype pyramid machine or a design for such a machine were present. Within the wide field of parallel architectures for image processing a new area was recently born and is growing healthily: the area of pyramidally structured multiprocessing systems. Essentially, the processors are arranged in planes (from a base to an apex) each one of which is generally a reduced (usually by a power of two) version of the plane underneath: these processors are horizontally interconnected (within a plane) and vertically connected with "fathers" (on top planes) and "children" on the plane below. This arrangement has a number of interesting features, all of which were amply discussed in our Workshop including the cellular array and hypercube versions of pyramids. A number of projects (in different parts of the world) are reported as well as some interesting applications in computer vision, tactile systems and numerical calculations.
Using a visual data analysis approach, wavelet concepts are explained in a way that is intuitive and easy to understand. Furthermore, in addition to wavelets, a whole range of related signal processing techniques such as wavelet packets, local cosine analysis, and matching pursuits are covered, and applications of wavelet analysis are illustrated -including nonparametric function estimation, digital image compression, and time-frequency signal analysis. This book and software package is intended for a broad range of data analysts, scientists, and engineers. While most textbooks on the subject presuppose advanced training in mathematics, this book merely requires that readers be familiar with calculus and linear algebra at the undergraduate level.
Computer vision deals with the problem of manipulating information contained in large quantities of sensory data, where raw data emerge from the transducing 6 7 sensors at rates between 10 to 10 pixels per second. Conventional general purpose computers are unable to achieve the computation rates required to op erate in real time or even in near real time, so massively parallel systems have been used since their conception in this important practical application area. The development of massively parallel computers was initially character ized by efforts to reach a speedup factor equal to the number of processing elements (linear scaling assumption). This behavior pattern can nearly be achieved only when there is a perfect match between the computational struc ture or data structure and the system architecture. The theory of hierarchical modular systems (HMSs) has shown that even a small number of hierarchical levels can sizably increase the effectiveness of very large systems. In fact, in the last decade several hierarchical architectures that support capabilities which can overcome performances gained with the assumption of linear scaling have been proposed. Of these architectures, the most commonly considered in com puter vision is the one based on a very large number of processing elements (PEs) embedded in a pyramidal structure. Pyramidal architectures supply the same image at different resolution lev els, thus ensuring the use of the most appropriate resolution for the operation, task, and image at hand.
This volume presents the proceedings of the 10th International Workshop on Combinatorial Image Analysis, held December 1–3, 2004, in Auckland, New Zealand. Prior meetings took place in Paris (France, 1991), Ube (Japan, 1992), Washington DC (USA, 1994), Lyon (France, 1995), Hiroshima (Japan, 1997), Madras (India, 1999), Caen (France, 2000), Philadelphia (USA, 2001), and - lermo (Italy, 2003). For this workshop we received 86 submitted papers from 23 countries. Each paper was evaluated by at least two independent referees. We selected 55 papers for the conference. Three invited lectures by Vladimir Kovalevsky (Berlin), Akira Nakamura (Hiroshima), and Maurice Nivat (Paris) completed the program. Conference papers are presented in this volume under the following topical part titles: discrete tomography (3 papers), combinatorics and computational models (6), combinatorial algorithms (6), combinatorial mathematics (4), d- ital topology (7), digital geometry (7), approximation of digital sets by curves and surfaces (5), algebraic approaches (5), fuzzy image analysis (2), image s- mentation (6), and matching and recognition (7). These subjects are dealt with in the context of digital image analysis or computer vision.
Parallel Computer Vision
This long-awaited update of Meyer's Wavelets : algorithms and applications includes completely new chapters on four topics: wavelets and the study of turbulence, wavelets and fractals (which includes an analysis of Riemann's nondifferentiable function), data compression, and wavelets in astronomy. The chapter on data compression was the original motivation for this revised edition, and it contains up-to-date information on the interplay between wavelets and nonlinear approximation. The other chapters have been rewritten with comments, references, historical notes, and new material. Four appendices have been added: a primer on filters, key results (with proofs) about the wavelet transform, a complete discussion of a counterexample to the Marr-Mallat conjecture on zero-crossings, and a brief introduction to Hölder and Besov spaces. In addition, all of the figures have been redrawn, and the references have been expanded to a comprehensive list of over 260 entries. The book includes several new results that have not appeared elsewhere.
The II international workshop on "Data Analysis in Astronomy" was intended to provide an overview on the state of the art and the trend in data analy sis and image processing in the context of their applications in Astronomy. The need for the organization of a second workshop in this subject derived from the steady. growing and development in the field and from the increasing cross-interaction between methods, technology and applications in Astronomy. The book is organized in four main sections: - Data Analysis Methodologies - Data Handling and Systems dedicated to Large Experiments - Parallel Processing - New Developments The topics which have been selected cover some of the main fields in data analysis in Astronomy. Methods that provide a major contribution to the physical interpretation of the data have been considered. Attention has been devoted to the description of the data analysis and handling organization in very large experiments. A review of the current major satellite and ground based experiments has been included. At the end of the book the following 'Panel Discussions' are included: - Data Analysis Trend in Optical and Radio Astronomy - Data Analysis Trend in X and Gamma Astronomy - Problems and Solutions in the Design of Very Large Experiments - Trend on Parallel Processing Algorithms These contributions in a sense summarize the 'live' reaction of the audience to the various topics.