Multidimensional Signal, Image, and Video Processing and Coding, Second Edition
This book gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms.
This book also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams.
New to this edition:
- New appendices on random processes, information theory
- New coverage of image analysis - edge detection, linking, clustering, and segmentation
- Expanded coverage on image sensing and perception, including color spaces.
- Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC.
- Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding.
- More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming.
- New coverage of super-resolution methods for image and video.
- Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected.
- New chapters on introductory random processes, information theory, and image enhancement and analysis
- Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC)
Why Read This Book
You should read this book if you want a unified, DSP-oriented treatment of image and video problems that bridges theory and practical coding/standards. It gives you both the mathematical foundations for multidimensional signals and hands-on perspectives (with MATLAB examples) for modern compression, restoration, and transmission methods.
Who Will Benefit
Graduate students, image/video engineers, and DSP practitioners who need a rigorous yet application-oriented reference on multidimensional signal processing and coding.
Level: Advanced — Prerequisites: Signals and systems (continuous/discrete), linear algebra, Fourier transforms, basic probability/random processes, and some programming familiarity (MATLAB recommended).
Key Takeaways
- Analyze sampling, aliasing, and reconstruction in 2-D and 3-D signal domains.
- Design and apply multidimensional transforms (2-D DFT/DCT and separable/nonseparable transforms) for representation and filtering.
- Implement wavelet and multiresolution methods for image compression and denoising.
- Explain and evaluate image and video coding standards (JPEG, JPEG2000 concepts, and modern video coding) and practical transmission considerations.
- Apply advanced restoration techniques such as super-resolution and non-local processing.
- Assess rate–distortion tradeoffs and basic network coding approaches for image/video transmission.
Topics Covered
- Introduction and overview of multidimensional signal processing
- Mathematical preliminaries and 2-D/3-D signal representations
- Sampling and reconstruction in multiple dimensions
- Multidimensional transforms: 2-D DFT, separable transforms, DCT
- Statistical models and random fields for images
- Information theory basics and rate–distortion concepts
- Predictive and transform coding for images
- Wavelets, multiresolution analysis, and JPEG2000 concepts
- Directional transforms, non-local methods, and sparse representations
- Image and video coding standards and practical coder architectures
- Restoration and super-resolution techniques
- Transmission, network coding, and robustness for image/video delivery
- MATLAB examples, case studies, and implementation notes
Languages, Platforms & Tools
How It Compares
More DSP- and coding-focused than Gonzalez & Woods' Digital Image Processing (which emphasizes elementary image processing and pedagogy); it offers deeper treatment of multidimensional transforms and modern coding/transmission aspects than many introductory texts.
