Mathematics of Digital Images

Creation, Compression, Restoration, Recognition

S.G. Hoggar

854 pages, parution le 23/08/2006

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Résumé

Compression, restoration and recognition are three of the key components of digital imaging. The mathematics needed to understand and carry out all these components are explained here in a style that is at once rigorous and practical with many worked examples, exercises with solutions, pseudocode, and sample calculations on images. The introduction lists fast tracks to special topics such as Principal Component Analysis, and ways into and through the book, which abounds with illustrations. The first part describes plane geometry and pattern-generating symmetries, along with some on 3D rotation and reflection matrices. Subsequent chapters cover vectors, matrices and probability. These are applied to simulation, Bayesian methods, Shannon's information theory, compression, filtering and tomography. The book will be suited for advanced courses or for self-study. It will appeal to all those working in biomedical imaging and diagnosis, computer graphics, machine vision, remote sensing, image processing and information theory and its applications.

Sommaire

Introduction
Isometries
How isometries combine
The braid patterns
Plane patterns and symmetries
The 17 plane patterns
More plane truth
Vectors and matrices
Matrix algebra
Probability
Random vectors
Sampling and inference
Entropy and coding
Information and error-correction
The Fourier transform
Transforming images
Scaling
B-spline wavelets
Further methods
References
Symbols
Selected answers
Index

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	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	S.G. Hoggar
Parution	23/08/2006
Nb. de pages	854
Format	19,5 x 25
Couverture	Relié
Poids	1776g
Intérieur	Noir et Blanc
EAN13	9780521780292
ISBN13	978-0-521-78029-2