Image Processing: Mathematical Methods and Applications

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Digital image processing technology has developed markedly over the last ten years, and more and more information is being conveyed through its display and analysis. The way in which image data is stored and processed is fundamental to all aspects of information technology. Examples include remote sensing using digital satellites; making diagnoses using conventional X-ray computed tomography; and research into the behavior of the human brain using magnetic resonance imaging. This book consists of twenty-one papers that collectively cover a broad range of image processing problems and the way in which their solutions are used in different areas of science and technology. The papers present details of the ways computers of varying processing power can be programmed to store images efficiently, resolve features and patterns that are either time consuming or impossible for humans to interpret, and develop machines that can "see" like humans. They also discuss a wide range of applications, including the use of lasers for studying dynamic behavior of mechanical components, and fractal geometry for recognizing patterns. The book will be useful to any engineer, scientist, and technologist interested in current research issues in image processing.

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Product Details

Table of Contents

I. Keynote paper
The evolution of an image processing language, W.O. Saxton
II. Mathematical techniques in image processing
Kramer's sampling theorem in signal analysis and its role in mathematics, P.L. Butzer and R. Nasri-Roudsari
Nonstandard methods in image processing, R.F. Hoskins
III. Inverse problems
Algebraic solutions to the non-stationary deconvolution problem, J.M. Blackledge and P.A. Lezeau
Restoration of 3D real images using projection onto convex sets, M. Razaz, R.A. Lee and P.J. Shaw
Comparison of iterative deconvolution and Wiener filtering for image restoration, M. Razaz and R.A. Lee
IV. Image data compression
Faster block coding of images using the truncation method, M.M. Anguh and R.R. Martin
Fractal image compression, M. Barnsley and L. Barnsley
Complexity reduction methods for fractal image compression, D. Saupe and R. Hamzaoui
V. Fractals and image processing
Jigsaws and faster fractal pictures, S.G. Hoggar and L. Menzies
Fractal dimension segmentation, J.M. Blackledge, B Foxon and S. Mikhailov
VI. Applications
Images of the Earth's surface and atmosphere, M.J. Rycroft
A goodness-of-fit measure applied to spectral mixture modelling, S.E. Hobbs and G. Thomas
Spatial data representation for rotation invariant correlation, J.M. Blackledge and D. Sapounas
Application of some image processing techniques to the B-scan analysis of two-phase flow, J.M. Blackledge
Estimating fractal dimension and number of degrees of freedom for multiphase flow regime identification, W. Rawes, G. Oddie and H. Yeung
Optoelectronic ESPI, R.P. Tatum
Probabilistic resolution criterion for imaging in scattering media, R.K. Appel, K.I. Hopcraft and M.G. Somekh
Analysis of color-level distribution in filter backwashing videos, C.S.B. Fitzpatrick
Digital image processing in medicine, N.G. Reading
Computer-based radiological training and education, N.P. Jeffery, et. al.

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