Burger / Burge Principles of Digital Image Processing

Advanced Methods
2013
ISBN: 978-1-84882-919-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 369 Seiten, eBook

Reihe: Undergraduate Topics in Computer Science

This easy-to-follow textbook is the third of three volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on which to build, and practitioners in search of critical analysis and concrete implementations of the most important techniques. This volume builds upon the introductory material presented in the first two volumes (Fundamental Techniques and Core Algorithms) with additional key concepts and methods in image processing.

Features and topics: practical examples and carefully constructed chapter-ending exercises drawn from the authors' years of experience teaching this material; real implementations, concise mathematical notation, and precise algorithmic descriptions designed for programmers and practitioners; easily adaptable Java code and completely worked-out examples for easy inclusion in existing (and rapid prototyping of new) applications; uses ImageJ, the image processing system developed, maintained, and freely distributed by the U.S. National Institutes of Health (NIH); provides a supplementary website with the complete Java source code, test images, and corrections—www.imagingbook.com; additional presentation tools for instructors including a complete set of figures, tables, and mathematical elements.

This thorough, reader-friendly text will equip undergraduates with a deeper understanding of the topic and will be invaluable for further developing knowledge via self-study.

Zielgruppe

Lower undergraduate

Autoren/Hrsg.

Burger, Wilhelm

Burge, Mark J.

Inhaltsverzeichnis

Introduction

Automatic Thresholding

Filters for Color Images

Edge Detection in Color Images

Edge-Preserving Smoothing Filters

Fourier Shape Descriptors

SIFT—Scale-Invariant Local Features

Mathematical Symbols and Notation

Vector Algebra and Calculus

Statistical Prerequisites

Gaussian Filters

Color Space Transformations