10-04-2014, 12:51 PM
Image registration methods: a survey
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Abstract
This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying
images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration
geometrically align two images (the reference and sensed images). The reviewed approaches are classified according to their nature (area-
based and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping
function design, and image transformation and resampling. Main contributions, advantages, and drawbacks of the methods are mentioned in
the paper. Problematic issues of image registration and outlook for the future research are discussed too. The major goal of the paper is to
provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas.
q 2003 Elsevier B.V. All rights reserved.
Introduction
Image registration is the process of overlaying two or
more images of the same scene taken at different times,
from different viewpoints, and/or by different sensors. It
geometrically aligns two images—the reference and
sensed images. The present differences between images
are introduced due to different imaging conditions. Image
registration is a crucial step in all image analysis tasks
in which the final information is gained from the
combination of various data sources like in image fusion,
change detection, and multichannel image restoration.
Typically, registration is required in remote sensing
(multispectral classification, environmental monitoring,
change detection, image mosaicing, weather forecasting,
creating super-resolution images, integrating information
into geographic information systems (GIS)), in medicine
(combining computer tomography (CT) and NMR data
to obtain more complete information about the patient,
monitoring tumor growth, treatment verification,
comparison of the patient’s data with anatomical atlases)
Image registration methodology
Image registration, as it was mentioned above, is widely
used in remote sensing, medical imaging, computer vision
etc. In general, its applications can be divided into four main
groups according to the manner of the image acquisition:
Different viewpoints (multiview analysis). Images of the
same scene are acquired from different viewpoints. The aim
is to gain larger a 2D view or a 3D representation of the
scanned scene.
Examples of applications: Remote sensing—mosaicing
of images of the surveyed area. Computer vision—shape
recovery (shape from stereo).
Different times (multitemporal analysis). Images of the
same scene are acquired at different times, often on regular
basis, and possibly under different conditions. The aim is to
find and evaluate changes in the scene which appeared
between the consecutive image acquisitions.
Feature matching
The detected features in the reference and sensed images
can be matched by means of the image intensity values in
their close neighborhoods, the feature spatial distribution, or
the feature symbolic description. Some methods, while
looking for the feature correspondence, simultaneously
estimate the parameters of mapping functions and thus
merge the second and third registration steps.
In the following paragraphs, the two major categories
(area-based and feature-based methods, respectively), are
retained and further classified into subcategories according
to the basic ideas of the matching methods.