1st Edition

A Concise Introduction to Image Processing using C++

By Meiqing Wang, Choi-Hong Lai Copyright 2009
    268 Pages 70 B/W Illustrations
    by Chapman & Hall

    Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, allowing you to easily apply these techniques in real-world problems.

    The book presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations (PDEs), and new image compression methods, such as fractal image compression and wavelet compression. It begins with coverage of representation, and then moves on to communications and processing. It concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. The accompanying downloadable resources contain code for all algorithms.

    Suitable as a text for any course on image processing, the book can also be used as a self-study resource for researchers who need a concise and clear view of current image processing methods and coding examples. The authors introduce mathematical concepts with rigor suitable for readers with some background in calculus, algebra, geometry, and PDEs. All algorithms described are illustrated with code implementation and many images compare the results of different methods. The inclusion of C++ implementation code for each algorithm described enables students and practitioners to build up their own analysis tool.

    Basic Concepts of Images

    Analogue Signals

    Digital Signals

    Grey-Scale Images

    Colour Images

    Image Storage Formats

    Video

    Exercises

    References

    Partial Code Examples

     

    Basic Image Processing Tools

    Correlation Operation and Convolution Operation

    Fourier Transform

    The Discrete Cosine Transform

    The Gabor Transform

    The Wavelet Transform

    Further Reading: Orthogonality and Completeness

    Exercises

    References

    Partial Code Examples

    Preprocessing Techniques for Images

    Pixel Brightness (Grey-Level) Transformations

    Concepts and Models of Image Preprocessing

    Image Smoothing

    Image Enhancement

    Image Restoration

    Processing Methods Using Partial Differential Equations

    Further Reading

    Exercises

    References

    Partial Code Examples

    Image Segmentation

    Thresholding

    Edge-Based Segmentation

    Region-Based Segmentation

    Further Reading

    Exercises

    References

    Partial Code Examples

    Mathematical Morphology

    Some Basic Concepts of Set Theory

    Morphology for Binary Images

    Morphology for Grey-Scale Images

    Further Reading

    Exercises

    References

    Partial Code Examples

    Image Compression

    Image Fidelity Metrics

    Lossless Compression

    Lossy Compression

    Image Compression Standards: JPEG and MPEG

    Further Reading

    Exercises

    References

    Partial Code Examples

    Index

    Biography

    Meiqing Wang, Choi-Hong Lai

    "This book is exactly what the title says: a very brief outline of the most popular methods used in image processing. Each chapter contains the absolute essentials of the subject with a large set of examples at the end and, of course, C++ code. … the book could be used as a quick guide to the most standard image processing techniques."
    —Leslie P. Piegl, Zentralblatt MATH 1171

    "This book presents a compact overview of the current methods used in modern computer image processing and their applications. … All chapters are accompanied by C++ implementation of the method. This book requires only some background in geometry, algebra, and calculus and can serve as an excellent starting book for anyone who needs to become familiar with current methods in the field of image processing."
    EMS Newsletter, June 2009