Novel Pixel-Level and Subpixel-Level Registration Algorithms for Multi-Modal Imagery Data
type: CreativeWork
description: Image registration is an important pre-processing operation to be performed before many image exploitation and processing functions such as data fusion, and super-resolution frame. Given two image frames, obtained from the same sensor or from different sensors, the registration problem involves determining the transformation that most nearly maps (or aligns) one image frame into the other. Typically, image registration requires intensive computational effort and the developed techniques are scene dependent. Furthermore, the problems of multimodal image registration (i.e. problem of registering images acquired from dissimilar sensors) and sub-pixel image registration (i.e. registering two images at sub-pixel accuracy) are highly challenging and no satisfactory solutions exist.This dissertation introduces novel techniques to solve the image registration problem both at the pixel-level and at the sub-pixel level. For pixel-level registration, a procedure is offered that enjoys the advantages that it is not scene dependent and provides the same level of accuracy for registering images acquired from different types of sensors. The new technique is based on obtaining the local frequency content of an image and using this local frequency representation to extract control points for establishing correspondence. To extract the local frequency representation of an image, a computationally efficient scheme based on minimizing the latency of a Gabor filter bank by exploiting certain biological considerations is presented. The dissertation also introduces an extension of using local frequency to solve the sub-pixel image registration problem. The new algorithm is based on using the scaled local frequency representation of the images to be registered, with computationally inexpensive scaling of the local frequency of the images prior to correlation matching. Finally, this dissertation provides a novel approach to solve the problem of multi-modal image registration. The principal …
abstract: Image registration is an important pre-processing operation to be performed before many image exploitation and processing functions such as data fusion, and super-resolution frame. Given two image frames, obtained from the same sensor or from different sensors, the registration problem involves determining the transformation that most nearly maps (or aligns) one image frame into the other. Typically, image registration requires intensive computational effort and the developed techniques are scene dependent. Furthermore, the problems of multimodal image registration (i.e. problem of registering images acquired from dissimilar sensors) and sub-pixel image registration (i.e. registering two images at sub-pixel accuracy) are highly challenging and no satisfactory solutions exist.This dissertation introduces novel techniques to solve the image registration problem both at the pixel-level and at the sub-pixel level. For pixel-level registration, a procedure is offered that enjoys the advantages that it is not scene dependent and provides the same level of accuracy for registering images acquired from different types of sensors. The new technique is based on obtaining the local frequency content of an image and using this local frequency representation to extract control points for establishing correspondence. To extract the local frequency representation of an image, a computationally efficient scheme based on minimizing the latency of a Gabor filter bank by exploiting certain biological considerations is presented. The dissertation also introduces an extension of using local frequency to solve the sub-pixel image registration problem. The new algorithm is based on using the scaled local frequency representation of the images to be registered, with computationally inexpensive scaling of the local frequency of the images prior to correlation matching. Finally, this dissertation provides a novel approach to solve the problem of multi-modal image registration. The principal …
author: Elbakary, Mohamed Ibrahim
language: EN
keywords: image registration, image fusion
date published: 2005
date modified: 2026-07-24T00:55:10Z
provider: University of Arizona
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: The University of Arizona.

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10150/195712