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Digital Image Processing: Mathematical and Computational Methods [NOOK Book]

Overview

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. This book relates the methods of processing and interpreting digital images to the ‘physics’ of imaging ...
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Digital Image Processing: Mathematical and Computational Methods

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Overview

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. This book 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.

  • Provides mathematical methods required to describe images, image formation and different imaging systems
  • Outlines the principle techniques used for processing digital images
  • Relates the methods of processing and interpreting digital images to the ‘physics’ of imaging systems
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Product Details

Meet the Author

Jonathan M. Blackledge, Loughborough University, UK
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Table of Contents

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.
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