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11 - On the use of wavelets for image registration

from PART III - Feature Matching and Strategies for Image Registration

Published online by Cambridge University Press:  03 May 2011

By
Jacqueline Le Moigne ,
Ilya Zavorin  and
Harold Stone
Edited by
Jacqueline Le Moigne ,
Nathan S. Netanyahu  and
Roger D. Eastman
Jacqueline Le Moigne
Affiliation:
NASA Goddard Space Flight Center, Maryland
Ilya Zavorin
Affiliation:
University of Maryland, Maryland
Harold Stone
Affiliation:
NEC Research Laboratory Retiree, New Jersey
Jacqueline Le Moigne
Affiliation:
NASA-Goddard Space Flight Center
Nathan S. Netanyahu
Affiliation:
Bar-Ilan University, Israel and University of Maryland, College Park
Roger D. Eastman
Affiliation:
Loyola University Maryland
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Summary

Abstract

Wavelets provide a multiresolution description of images according to a well-chosen division of the space-frequency plane. This description provides information about various features present in the images that can be utilized to perform registration of remotely sensed images. In the last few years, many wavelet filters have been proposed for applications such as compression; in this chapter, we review the general principle of wavelet decomposition and the many filters that have been proposed for wavelet transforms, as they apply to image registration. In particular, we consider orthogonal wavelets, spline wavelets, and two pyramids obtained from a steerable decomposition. These different filters are studied and compared using synthetic datasets generated from a Landsat-Thematic Mapper (TM) scene.

Introduction

The main thrust of this chapter is to describe image registration methods that focus on computational speed and on the ability of handling multisensor data. As was described in Chapter 1 and in Brown (1992), any image registration method can be described by a feature space, a search space, a search strategy, and a similarity metric. Utilizing wavelets for image registration not only defines the type of features that will be matched, but it also enables the matching process to follow a multiresolution search strategy. Such an iterative matching at multiple scales represents one of the main factors that will define the accuracy of such methods.

Type
Chapter
Information
Image Registration for Remote Sensing , pp. 240 - 264
Publisher: Cambridge University Press
Print publication year: 2011

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References

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