Mathematical Foundations Of Image Processing And Analysis

Author: Jean-Charles Pinoli
Publisher: John Wiley & Sons
ISBN: 1118984552
Size: 39.35 MB
Format: PDF, Mobi
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Mathematical Foundations Of Image Processing And Analysis from the Author: Jean-Charles Pinoli. Mathematical Imaging is currently a rapidly growing field in applied mathematics, with an increasing need for theoretical mathematics. This book, the second of two volumes, emphasizes the role of mathematics as a rigorous basis for imaging sciences. It provides a comprehensive and convenient overview of the key mathematical concepts, notions, tools and frameworks involved in the various fields of gray-tone and binary image processing and analysis, by proposing a large, but coherent, set of symbols and notations, a complete list of subjects and a detailed bibliography. It establishes a bridge between the pure and applied mathematical disciplines, and the processing and analysis of gray-tone and binary images. It is accessible to readers who have neither extensive mathematical training, nor peer knowledge in Image Processing and Analysis. It is a self-contained book focusing on the mathematical notions, concepts, operations, structures, and frameworks that are beyond or involved in Image Processing and Analysis. The notations are simplified as far as possible in order to be more explicative and consistent throughout the book and the mathematical aspects are systematically discussed in the image processing and analysis context, through practical examples or concrete illustrations. Conversely, the discussed applicative issues allow the role of mathematics to be highlighted. Written for a broad audience – students, mathematicians, image processing and analysis specialists, as well as other scientists and practitioners – the author hopes that readers will find their own way of using the book, thus providing a mathematical companion that can help mathematicians become more familiar with image processing and analysis, and likewise, image processing and image analysis scientists, researchers and engineers gain a deeper understanding of mathematical notions and concepts.

Digital Signal And Image Processing Using Matlab Volume 2

Author: GĂ©rard Blanchet
Publisher: John Wiley & Sons
ISBN: 1848216416
Size: 18.34 MB
Format: PDF, ePub, Docs
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Digital Signal And Image Processing Using Matlab Volume 2 from the Author: Gérard Blanchet. Volume 2 of the second edition of the fully revised and updated Digital Signal and Image Processing using MATLAB® is essentially a collection of examples and exercises which also presents applications of digital signal- or image processing, and techniques which were not touched upon in the previous volume. It will be of particular benefit to readers who already possess a good knowledge of MATLAB®, a command of the fundamental elements of digital signal processing and who are familiar with both the fundamentals of continuous-spectrum spectral analysis and who have a certain mathematical knowledge concerning Hilbert spaces. More than 200 programs and functions are provided in the MATLAB language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.

Color Image And Video Enhancement

Author: Emre Celebi
Publisher: Springer
ISBN: 3319093630
Size: 52.11 MB
Format: PDF, ePub, Docs
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Color Image And Video Enhancement from the Author: Emre Celebi. This text covers state-of-the-art color image and video enhancement techniques. The book examines the multivariate nature of color image/video data as it pertains to contrast enhancement, color correction (equalization, harmonization, normalization, balancing, constancy, etc.), noise removal and smoothing. This book also discusses color and contrast enhancement in vision sensors and applications of image and video enhancement.

Mathematical Problems In Data Science

Author: Li M. Chen
Publisher: Springer
ISBN: 3319251279
Size: 60.78 MB
Format: PDF, ePub, Docs
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Mathematical Problems In Data Science from the Author: Li M. Chen. This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book includes possible solutions and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets and partial-connectedness among data points or data sets. Discussions also cover the completion problem of Netflix matrix; machine learning method on massive data sets; image segmentation and video search. This book introduces software tools for data science and Big Data such MapReduce, Hadoop, and Spark. This book contains three parts. The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical methods. The final section provides case studies on special topics in variational learning, manifold learning, business and financial data rec overy, geometric search, and computing models. Mathematical Problems in Data Science is a valuable resource for researchers and professionals working in data science, information systems and networks. Advanced-level students studying computer science, electrical engineering and mathematics will also find the content helpful.

Mathematical Foundations Of Scientific Visualization Computer Graphics And Massive Data Exploration

Author: Torsten Möller
Publisher: Springer Science & Business Media
ISBN: 3540499261
Size: 45.13 MB
Format: PDF, Kindle
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Mathematical Foundations Of Scientific Visualization Computer Graphics And Massive Data Exploration from the Author: Torsten Möller. The goal of visualization is the accurate, interactive, and intuitive presentation of data. Complex numerical simulations, high-resolution imaging devices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehension. The peer-reviewed state-of-the-art research papers included in this book focus on continuous data models, such as is common in medical imaging or computational modeling. From the viewpoint of a visualization scientist, we typically collaborate with an application scientist or engineer who needs to visually explore or study an object which is given by a set of sample points, which originally may or may not have been connected by a mesh. At some point, one generally employs low-order piecewise polynomial approximationsof an object, using one or several dependent functions. In order to have an understanding of a higher-dimensional geometrical “object” or function, ef?cient algorithms supporting real-time analysis and manipulation (- tation, zooming) are needed. Often, the data represents 3D or even time-varying 3D phenomena (such as medical data), and the access to different layers (slices) and structures (the underlying topology) comprising such data is needed.

Formal Concept Analysis

Author: Bernhard Ganter
Publisher: Springer Science & Business Media
ISBN: 3642598307
Size: 68.32 MB
Format: PDF, Docs
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Formal Concept Analysis from the Author: Bernhard Ganter. This first textbook on formal concept analysis gives a systematic presentation of the mathematical foundations and their relations to applications in computer science, especially in data analysis and knowledge processing. Above all, it presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge. The mathematical foundations are treated thoroughly and are illuminated by means of numerous examples, making the basic theory readily accessible in compact form.

Foundations Of Image Science

Author: Harrison H. Barrett
Size: 80.77 MB
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Foundations Of Image Science from the Author: Harrison H. Barrett. This text presents the fundamental physics at work in imaging systems. It offers a coherent treatment of the principles, mathematics and statistics needed to understand imaging systems.

Mathematical Foundations And Applications Of Graph Entropy

Author: Matthias Dehmer
Publisher: John Wiley & Sons
ISBN: 3527693254
Size: 37.80 MB
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Mathematical Foundations And Applications Of Graph Entropy from the Author: Matthias Dehmer. This latest addition to the successful Network Biology series presents current methods for determining the entropy of networks, making it the first to cover the recently established Quantitative Graph Theory. An excellent international team of editors and contributors provides an up-to-date outlook for the field, covering a broad range of graph entropy-related concepts and methods. The topics range from analyzing mathematical properties of methods right up to applying them in real-life areas. Filling a gap in the contemporary literature this is an invaluable reference for a number of disciplines, including mathematicians, computer scientists, computational biologists, and structural chemists.

Computer And Computing Technologies In Agriculture Ii Volume 2

Author: Daoliang Li
Publisher: Springer Science & Business Media
ISBN: 1441902104
Size: 40.72 MB
Format: PDF, Docs
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Computer And Computing Technologies In Agriculture Ii Volume 2 from the Author: Daoliang Li. The papers in this volume comprise the refereed proceedings of the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA2008), in Beijing, China, 2008. The conference on the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA 2008) is cooperatively sponsored and organized by the China Agricultural University (CAU), the National Engineering Research Center for Information Technology in Agriculture (NERCITA), the Chinese Society of Agricultural Engineering (CSAE) , International Federation for Information Processing (IFIP), Beijing Society for Information Technology in Agriculture, China and Beijing Research Center for Agro-products Test and Farmland Inspection, China. The related departments of China’s central government bodies like: Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Education and the Beijing Municipal Natural Science Foundation, Beijing Academy of Agricultural and Forestry Sciences, etc. have greatly contributed and supported to this event. The conference is as good platform to bring together scientists and researchers, agronomists and information engineers, extension servers and entrepreneurs from a range of disciplines concerned with impact of Information technology for sustainable agriculture and rural development. The representatives of all the supporting organizations, a group of invited speakers, experts and researchers from more than 15 countries, such as: the Netherlands, Spain, Portugal, Mexico, Germany, Greece, Australia, Estonia, Japan, Korea, India, Iran, Nigeria, Brazil, China, etc.