A Computational Introduction to Digital Image Processing, Second Edition

Alasdair McAndrew

November 5, 2015 by Chapman and Hall/CRC
Textbook - 535 Pages - 16 Color & 388 B/W Illustrations
ISBN 9781482247329 - CAT# K23626

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Features

  • Uses both open-source and commercial software (MATLAB®, GNU Octave, and Python) to provide a complete environment for image processing that is easy to use, explain, and extend
  • Presents a discrete mathematics approach that links the calculus-based (continuous) theory with its discrete implementation
  • Provides a strong connection between theory and practice, allowing students to develop their own functions for implementing specific image processing algorithms
  • Keeps the required mathematics for understanding image processing algorithms at the elementary undergraduate computer science level
  • Incorporates many examples of images accompanied with commands in each of the three software systems, enabling students to create the images from the text
  • Contains a variety of end-of-chapter exercises, including "pencil-and-paper" ones designed for better understanding of the material and computer-based problems for exploring the algorithms and methods
  • Includes the images and software functions in Python, MATLAB, and Octave on the author’s website

A solutions manual and figure slides are available upon qualifying course adoption.

Summary

Highly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial Software

A Computational Introduction to Digital Image Processing, Second Edition explores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Taking a strictly elementary perspective, the book only covers topics that involve simple mathematics yet offer a very broad and deep introduction to the discipline.

New to the Second Edition

This second edition provides users with three different computing options. Along with MATLAB®, this edition now includes GNU Octave and Python. Users can choose the best software to fit their needs or migrate from one system to another. Programs are written as modular as possible, allowing for greater flexibility, code reuse, and conciseness. This edition also contains new images, redrawn diagrams, and new discussions of edge-preserving blurring filters, ISODATA thresholding, Radon transform, corner detection, retinex algorithm, LZW compression, and other topics.

Principles, Practices, and Programming

Based on the author’s successful image processing courses, this bestseller is suitable for classroom use or self-study. In a straightforward way, the text illustrates how to implement imaging techniques in MATLAB, GNU Octave, and Python. It includes numerous examples and exercises to give students hands-on practice with the material.