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Digital Functions and Data Reconstruction : Digital-Discrete Methods / by Li Chen.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Author/Creator:
Chen, Li, 1961- author.
Contributor:
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Language:
English
Subjects (All):
Optical data processing.
Signal processing.
Image processing.
Speech processing systems.
Discrete mathematics.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Signal, Image and Speech Processing.
Discrete Mathematics.
Local Subjects:
Computer Imaging, Vision, Pattern Recognition and Graphics.
Signal, Image and Speech Processing.
Discrete Mathematics.
Physical Description:
1 online resource (XX, 208 pages)
Edition:
First edition 2013.
Contained In:
Springer eBooks
Place of Publication:
New York, NY : Springer New York : Imprint: Springer, 2013.
System Details:
text file PDF
Summary:
Digital Functions and Data Reconstruction: Digital-Discrete Methods provides a solid foundation to the theory of digital functions and its applications to image data analysis, digital object deformation, and data reconstruction. This new method has a unique feature in that it is mainly built on discrete mathematics with connections to classical methods in mathematics and computer sciences. Digitally continuous functions and gradually varied functions were developed in the late 1980s. A. Rosenfeld (1986) proposed digitally continuous functions for digital image analysis, especially to describe the "continuous" component in a digital image, which usually indicates an object. L. Chen (1989) invented gradually varied functions to interpolate a digital surface when the boundary appears to be continuous. In theory, digitally continuous functions are very similar to gradually varied functions. Gradually varied functions are more general in terms of being functions of real numbers; digitally continuous functions are easily extended to the mapping from one digital space to another. This will be the first book about digital functions, which is an important modern research area for digital images and digitalized data processing, and provides an introduction and comprehensive coverage of digital function methods. Digital Functions and Data Reconstruction: Digital-Discrete Methods offers scientists and engineers who deal with digital data a highly accessible, practical, and mathematically sound introduction to the powerful theories of digital topology and functional analysis, while avoiding the more abstruse aspects of these topics.
Contents:
Introduction
Functions and Relations
Functions in Digital and Discrete Space
Gradually Varied Extensions
Digital and Discrete Deformation
Basic Numerical and Computational Methods
Digital-Discrete Approaches for Smooth Functions
Digital-Discrete Methods for Data Reconstruction
Harmonic Functions for Data Reconstruction on 3D Manifolds
Gradual Variations and Partial Differential Equations
Gradually Varied Functions for Advanced Computational Methods
Digital-Discrete Method and Its Relations to Graphics and AI Methods.
Other Format:
Printed edition:
ISBN:
978-1-4614-5638-4
9781461456384
Access Restriction:
Restricted for use by site license.

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