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Image Processing : Tensor Transform and Discrete Tomography with MATLAB ®

By: Artyom M. Grigoryan (Author) , Merughan M. Grigoryan (Author)

Manufacture on Demand

Ksh 51,950.00

Format: Hardback or Cased Book

ISBN-10: 1466509945

ISBN-13: 9781466509948

Publisher: Taylor & Francis Inc

Imprint: CRC Press Inc

Country of Manufacture: US

Country of Publication: GB

Publication Date: Oct 15th, 2012

Publication Status: Active

Product extent: 468 Pages

Weight: 828.00 grams

Dimensions (height x width x thickness): 24.00 x 16.10 x 3.10 cms

Product Classification / Subject(s): Image processing

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  • Description

  • Reviews

Focusing on mathematical methods in computer tomography, this book introduces novel approaches to help solve the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along parallel rays to more accurately reconstruct images from a finite number of projections and avoid overradiating the body during a CT scan. The book presents several new concepts and methods, including 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.

Focusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB® 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®-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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