A Concise Introduction to Image Processing Using C++

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 CD-ROM contains 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