Image Registration Using Redundant Wavelet Transforms (Paperback)


Imagery is collected much faster and in significantly greater quantities today compared to a few years ago. Accurate registration of this imagery is vital for comparing the similarities and differences between multiple images. Image registration is a significant component in computer vision and other pattern recognition problems, medical applications such as Medical Resonance Images (MRI) and Positron Emission Tomography (PET), remotely-sensed data for target location and identification, and super-resolution algorithms. Since human analysis is tedious and error prone for large data sets, we require an automatic, effcient, robust, and accurate method to register images. Wavelet transforms have proven useful for a variety of signal and image processing tasks, including image registration. In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and improve processing efficiency.

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Product Description

Imagery is collected much faster and in significantly greater quantities today compared to a few years ago. Accurate registration of this imagery is vital for comparing the similarities and differences between multiple images. Image registration is a significant component in computer vision and other pattern recognition problems, medical applications such as Medical Resonance Images (MRI) and Positron Emission Tomography (PET), remotely-sensed data for target location and identification, and super-resolution algorithms. Since human analysis is tedious and error prone for large data sets, we require an automatic, effcient, robust, and accurate method to register images. Wavelet transforms have proven useful for a variety of signal and image processing tasks, including image registration. In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and improve processing efficiency.

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Product Details

General

Imprint

Biblioscholar

Country of origin

United States

Release date

November 2012

Availability

Expected to ship within 10 - 15 working days

First published

November 2012

Authors

Dimensions

246 x 189 x 5mm (L x W x T)

Format

Paperback - Trade

Pages

94

ISBN-13

978-1-288-31989-3

Barcode

9781288319893

Categories

LSN

1-288-31989-4



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