One-and-Multidimensional Signal Processing: Algorithms and Applications in Image Processing
With the constant increase in applications involving image processing and multimedia procedures digital signal processing (DSP) is important for modern information engineering. One-- and Multidimensional Signal Processing provides an introduction to the algorithmic basics of image and TV communication systems as well as for systems in automation and robotic applications using sensor based imaging techniques. This novel combination of both one-- and multidimensional signal processing discusses the similarities between the two and aids the understanding of one theory over the other. aeo Presents an applications--oriented approach to image processing including TV signal processing and discusses image scanning and the use of DSP procedures or digital filters aeo Provides clear and comprehensive coverage of basic concepts such as spatial frequency, spatio--temporal signal processing and the spectral representation of motion and tracking of moving objects aeo Features examples of applications including image pick--up and display as well as still image filtering and image sequence interpolation aeo Introduces new design strategies for finite--impulse response (FIR) filters for image processing applciations using spatial and frequency design constraints aeo Includes an introduction to nonlinear image processing techniques applying edge detection operators, morphological operators and rank order filters Such a practical book will have wide--ranging appeal as a valuable resource for researchers and developers and as an ideal introductory text for senior undergraduate and postgraduate students.
Why Read This Book
You should read this book if you want a DSP-centered bridge between familiar 1D signal processing concepts and their multidimensional (image/TV) counterparts — it emphasizes algorithms and practical applications. You will get clear explanations of 2D transforms, filtering, sampling and scanning issues framed so you can transfer DSP intuition from time signals to images and sensor arrays.
Who Will Benefit
Practicing engineers and graduate students with basic DSP background who are implementing or researching image/TV processing algorithms, sensor-based imaging, or multidimensional filtering.
Level: Intermediate — Prerequisites: Basic signals & systems and DSP (Fourier transform, convolution), linear algebra, and familiarity with discrete-time filtering; MATLAB or similar tool experience is helpful but not required.
Key Takeaways
- Understand how 1D DSP concepts (sampling, filtering, transforms) extend to two and higher dimensions
- Design and analyze separable and nonseparable 2D digital filters for image processing
- Apply 2D Fourier and DFT/FFT techniques to image spectral analysis and filtering
- Implement practical image scanning and TV signal processing methods used in acquisition and transmission
- Use multirate and subband ideas in the context of images for efficient processing
- Diagnose and correct common image degradation via restoration and enhancement algorithms
Topics Covered
- Introduction: Motivation and overview of one- and multidimensional signal processing
- Review of 1D signals and systems for DSP practitioners
- Sampling theory: 1D to multidimensional sampling and aliasing
- Multidimensional transforms: 2D Fourier transform and discrete transforms
- 2D DFT/FFT algorithms and efficient implementation
- Two-dimensional digital filter design: separable and nonseparable filters
- Image scanning, TV signal formats and practical acquisition issues
- Multirate and subband processing for images
- Image enhancement and restoration using DSP techniques
- Applications in automation, robotics and sensor-based imaging
- Implementation considerations and examples (algorithmic notes)
Languages, Platforms & Tools
How It Compares
Compared with Gonzalez & Woods' Digital Image Processing, Schroder places more emphasis on DSP algorithms and the theoretical continuity between 1D and multidimensional signal processing rather than a broad survey of image-processing applications.
