Image Processing: The Fundamentals
Image Processing The Fundamentals Maria Petrou, University of Surrey, Guildford, UK Panagiota Bosdogianni, Technical University of Crete, Chania, Greece Image processing has been one of the most active areas of research in recent years. The techniques involved have found significant applications in areas as diverse as video-conferencing, image communication, robotics, geoscience and medicine. From intelligent cars that drive themselves to key-hole surgery, this enormous impact on society is expected to change our lives radically. Providing a step by step guide to the basic principles underlying all image processing tasks, this volume is the result of 11 years of teaching experience.
* Features numerous worked examples, guiding the reader through the intricacies of reaching the solutions.
* Explains the concepts introduced using small sized images that the reader can manipulate without the use of computers.
* Allows the reader to appreciate the 'nuts and bolts' of each method, the issues involved and the problems that may be encountered in real applications.
* Presents detailed mathematical explanations at two levels - an easy-to-follow narrative with minimum use of mathematics, and a higher level that uses mathematical rigour.
Image Processing: The Fundamentals is an ideal self-teaching aide and will prove an invaluable companion for research students in related fields. Alternative techniques are demonstrated for each image allowing the reader to appreciate subtle differences between them. Visit Our Web Page! http://www.wiley.com/
Why Read This Book
You should read this book if you want a clear, worked-example driven introduction to the mathematical and algorithmic foundations of image processing; it links 2-D signal concepts and Fourier analysis to practical tasks like filtering, restoration, edge detection and segmentation. The text is compact and pedagogical, so you will get hands-on insight and intuition without wading through encyclopedic coverage.
Who Will Benefit
Students, engineers, and DSP practitioners with some mathematical background who need a readable, example-rich introduction to core image-processing methods and their links to 2-D signal processing.
Level: Intermediate — Prerequisites: Linear algebra, basic calculus and probability, and familiarity with 1-D signals and Fourier analysis; some exposure to MATLAB (or another numerical tool) is helpful but not required.
Key Takeaways
- Understand 2-D image sampling, quantization, and the implications of discrete representation
- Apply the 2-D Fourier transform and DFT to analyze and manipulate spatial-frequency content
- Design and implement basic spatial and frequency-domain filters for denoising and enhancement
- Implement and evaluate edge detection, feature extraction and segmentation algorithms
- Use morphological operators for shape-based processing and binary image analysis
- Apply multiresolution and wavelet concepts for image analysis and simple compression/restoration tasks
Topics Covered
- Introduction and scope of image processing
- Image representation, sampling and quantization
- Mathematical preliminaries: matrices, transforms and probability
- 2-D Fourier transform and the discrete Fourier transform
- Image enhancement and filtering in spatial and frequency domains
- Image restoration and noise models
- Edge detection and feature extraction
- Segmentation techniques
- Texture analysis and classification
- Mathematical morphology
- Multiresolution analysis and wavelets
- Selected applications and worked examples
Languages, Platforms & Tools
How It Compares
Covers many of the same fundamentals as Gonzalez & Woods' Digital Image Processing but is more compact and example-focused; less comprehensive as a reference, but often clearer for teaching core concepts.
