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7 - Registration of multiview images

from PART III - Feature Matching and Strategies for Image Registration

Published online by Cambridge University Press:  03 May 2011

By
A. Ardeshir Goshtasby
Edited by
Jacqueline Le Moigne ,
Nathan S. Netanyahu  and
Roger D. Eastman
A. Ardeshir Goshtasby
Affiliation:
Wright State University, Ohio
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

Multiview images of a 3D scene contain sharp local geometric differences. To register such images, a transformation function is needed that can accurately model local geometric differences between the images. A weighted linear transformation function for the registration of multiview images is proposed. Properties of this transformation function are explored and its accuracy in image registration is compared with accuracies of other transformation functions.

Introduction

Due to the acquisition of satellite images at a high altitude and relatively low resolution, overlapping images have very little to no local geometric differences, although global geometric differences may exist between them. Surface spline (Goshtasby, 1988) and multiquadric (Zagorchev and Goshtasby, 2006) transformation functions have been found to effectively model global geometric differences between overlapping satellite images.

High-resolution multiview images of a scene captured by low-flying aircrafts contain considerable local geometric differences. Local neighborhoods in the scene may appear differently in multiview images due to variation in local scene relief and difference in imaging view angle. Global transformation functions that successfully registered satellite images might not be able to satisfactorily register multiview aerial images.

A new transformation function for the registration of multiview aerial images is proposed. The transformation function is defined by a weighted sum of linear functions, each containing information about the geometric difference between corresponding local neighborhoods in the images.

Type
Chapter
Information
Image Registration for Remote Sensing , pp. 153 - 178
Publisher: Cambridge University Press
Print publication year: 2011

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