This authoritative text (the second part of a complete MSc course) provides mathematical methods required to describe images, image formation and different imaging systems, coupled with the principle techniques used for processing digital images. It is based on a course for postgraduates reading physics, electronic engineering, telecommunications engineering, information technology and computer science. Digital Image Processing: Mathematical and Computational Methods relates the methods of processing and interpreting digital images to the 'physics' of imaging systems. Case studies reinforce the methods discussed, with examples of current research themes.
Part 1 Mathematical and computational background
- Vector fields
- 2D Fourier theory
- The 2D DFT, FFT and FIR filter
- Field and wave equations
- Green functions
Part 2 Imaging systems modelling
- Scattering theory
- Imaging of layered media
- Projection tomography
- Diffraction tomography
- Synthetic aperture imaging
- Optical image formation
Part 3 Digital image processing methods
- Image restoration and reconstruction
- Reconstruction of band-limited images
- Bayesian estimation methods
- Image enhancement
Part 4 Pattern recognition and computer vision
- Segmentation and edge detection
- Statistical modelling and analysis
- Fractal images and image processing
- Coding and compression
- Supplementary problems
- Solutions and index