A Computational Introduction to Digital Image Processing (Paperback)
Alasdair McAndrew
Sold by AussieBookSeller, Truganina, VIC, Australia
AbeBooks Seller since June 22, 2007
New - Soft cover
Condition: New
Quantity: 1 available
Add to basketSold by AussieBookSeller, Truganina, VIC, Australia
AbeBooks Seller since June 22, 2007
Condition: New
Quantity: 1 available
Add to basketPaperback. Highly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial SoftwareA 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 EditionThis 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 ProgrammingBased on the authors 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. This bestseller explores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Along with MATLAB, this second edition now includes GNU Octave and Python. Programs are written as modular as possible, allowing for greater flexibility, code reuse, and conciseness. This edition also contains new Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Seller Inventory # 9780367783334
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.
Alasdair McAndrew is a senior lecturer and discipline leader in mathematics and physics at Victoria University in Melbourne, Australia. His teaching and research interests include image processing, cryptography, mathematics, and mathematics education. An avid technophile, he is the author of the CRC Press book Introduction to Cryptography with Open-Source Software. He holds a PhD from Monash University.
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