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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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Image Processing - Tensor Transform and Discrete Tomography with MATLAB (R) (Paperback)
Loot Price: R2,460
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Image Processing - Tensor Transform and Discrete Tomography with MATLAB (R) (Paperback)
Expected to ship within 12 - 19 working days
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Focusing on mathematical methods in computer tomography, Image
Processing: Tensor Transform and Discrete Tomography with MATLAB
(R) introduces novel approaches to help in solving the problem of
image reconstruction on the Cartesian lattice. Specifically, it
discusses methods of image processing along parallel rays to more
quickly and accurately reconstruct images from a finite number of
projections, thereby avoiding overradiation of the body during a
computed tomography (CT) scan. The book presents several new ideas,
concepts, and methods, many of which have not been published
elsewhere. New concepts include methods of transferring the
geometry of rays from the plane to the Cartesian lattice, the point
map of projections, the particle and its field function, and the
statistical model of averaging. The authors supply numerous
examples, MATLAB (R)-based programs, end-of-chapter problems, and
experimental results of implementation. The main approach for image
reconstruction proposed by the authors differs from existing
methods of back-projection, iterative reconstruction, and Fourier
and Radon filtering. In this book, the authors explain how to
process each projection by a system of linear equations, or linear
convolutions, to calculate the corresponding part of the 2-D tensor
or paired transform of the discrete image. They then describe how
to calculate the inverse transform to obtain the reconstruction.
The proposed models for image reconstruction from projections are
simple and result in more accurate reconstructions. Introducing a
new theory and methods of image reconstruction, this book provides
a solid grounding for those interested in further research and in
obtaining new results. It encourages readers to develop effective
applications of these methods in CT.
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