Understanding Image Registration

Isaac Pelchat (Editor)

Series: Computer Science, Technology and Applications
BISAC: COM016000

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$82.00

Volume 10

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Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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In Understanding Image Registration, two applications of image registration are discussed: the retinal image registration method and the far infrared image registration method. Many applications such as aerial photography and other wide-field-of-view image registering techniques can benefit from said methods.

Following this, in order to compare the performance of image registration using sparse coding with other non-sparse registration methods, a simulated transformation is utilized. Even in the presence of bias field distortion, the proposed method aligns images without any preprocessing for bias field correction.

The concluding study focuses on how the concept of a Gelfand pair from the theory of noncommutative harmonic analysis points to a two-step procedure. It introduces the Méndez transform that finds a partial solution to a registration problem, and the remaining problem can then be solved more easily using well-known methods.
(Imprint: Novinka)

Preface

Chapter 1. Image Registration for Retinal and FIR Images
(Fan Guo and Jin Tang, Department of Artificial Intelligence, Central South University, Changsha, Hunan, China)

Chapter 2. Image Registration Using Sparse Coding
(Maryam Afzali and Hamid Soltanian-Zadeh, 1Cardiff University Brain Research Imaging Center, School of Psychology, Cardiff University, Cardiff, Wales)

Chapter 3. Noncommutative Image Registration and the Méndez Transform
(Andreas Müller, University of Applied Sciences Rapperswil, Rapperswil-Jona, Switzerland)

Index

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