Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Over the years, a broad range of techniques have been developed for the various types of data and problems. These techniques have been independently studied for several different applications resulting in a large body of research. This paper organizes this material by establishing the relationship between the distortions in the image and the type of registration techniques which are most suitable. Two major types of distortions are distinguished. The first type are those which are the source of misregistration, i.e., they are the cause of the misalignment between the two images. Distortions which are the source of misregistration determine the transformation class which will optimally align the two images. The transformation class in turn influences the general technique that should be taken....

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 (areabased 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.

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Image warping has many applications in art as well as in image processing. Usually, displacements are computed with mathematical functions or by transformations of a triangulation of control points. Here, different approaches based on scattered data interpolation methods are presented. These methods provide smooth deformations with easily controllable behavior. The usefulness and performance of some selected classes of scattered data interpolation methods in this context is analyzed.

Introduction The ever expanding gamut of medical imaging techniques provides the clinician an increasingly multifaceted view of brain function and anatomy. The information provided by the various imaging modalities is often complementary (i.e. provides separate but useful information) and synergistic (i.e. the combination of information provides useful extra information). For example, X-ray computed tomography (CT) and magnetic resonance (MR) imaging exquisitely demonstrate brain anatomy but provide little functional information. Positron emission tomography (PET) and single photon emission computed tomography (SPECT) scans display aspects of brain function and allow metabolic measurements but poorly delineate anatomy. Furthermore, CT and MR images describe complementary morphologic features. For example, bone and calcifications are best seen on CT images, while soft-tissue structures are better differentiated by MR imaging. Clinical diagnosis and therapy planning and evaluatio

Recent growth of the geospatial information on the web has made it possible to easily access various maps and orthoimagery. By integrating these maps and imagery, we can create intelligent images that combine the visual appeal and accuracy of imagery with the detailed attribution information often contained in diverse maps. However, accurately integrating maps and imagery from different data sources remains a challenging task. This is because spatial data obtained from various data sources may have different projections and different accuracy levels. Most of the existing algorithms only deal with vector to vector spatial data integration or require human intervention to accomplish imagery to map conflation. In this paper, we describe an information integration approach that utilizes common vector datasets as "glue " to automatically conflate imagery with street maps. We present efficient techniques to automatically extract road intersections from imagery and maps as control points. We also describe a specialized point pattern matching algorithm to align the two point sets and conflation techniques to align the imagery with maps. We show that these automatic conflation techniques can automatically and accurately align maps with images of the same area. In particular, using the approach described in this paper, our system automatically aligns a set of TIGER maps for an area in El Segundo, CA to the corresponding orthoimagery with an average error of 8.35 meters per pixel. This is a significant improvement considering that simply combining the TIGER maps with the corresponding imagery based on geographic coordinates provided by the sources results in error of 27 meters per pixel.

Abstract–Transformation functions play a major role in nonrigid image registration. In this pa-per, the characteristics of thin-plate spline (TPS), multiquadric (MQ), piecewise linear (PL), and weighted mean (WM) transformations are explored and their performances in nonrigid image reg-istration are compared. TPS and MQ are found to be most suitable when the set of control-point correspondences is not large (fewer than a thousand) and variation in spacing between the control points is not large. When spacing between the control points varies greatly, PL is found to produce a more accurate registration than TPS and MQ. When a very large set of control points is given and the control points contain positional inaccuracies, WM is preferred over TPS, MQ, and PL because it uses an averaging process that smoothes the noise and does not require the solution of a very large system of equations. Use of transformation functions in the detection of incorrect correspondences is also discussed. Index Terms–Image registration, transformation function, thin-plate spline, multiquadric, radial basis functions, piecewise linear, weighted-mean

Deformed cross-dissolves are methods for inconspicuous interpolation between images. We describe algorithms for deformation based on scattered data interpolation methods and an improved cross-dissolve algorithm offering better performance than a normal bidirectional cross-dissolve. Results for interpolation in the field of medical visualization are presented.

Abstract We present a new approach for aligning families of 2D gels. Instead of choosing one of the gels as reference and performing pairwise alignment, we construct an ideal gel that is representative for the entire family and obtain a set of piecewise affine transformations that optimally align each gel of the family to the ideal gel. The coefficients defining the transformations as well as the ideal landmarks are obtained as the solution of a large-scale quadratic programming problem that can be solved efficiently by interiorpoint methods. 1 Proteomics and 2-D PAGE Proteome analysis involves the separation, visualization and analysis of complex mixtures containing as many as several thousand proteins obtained from whole cells, tissues or organisms. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), first introduced by O’Farrell [9] and Klose [8] in 1975, remains a core technology for separating complex protein mixtures in the majority of proteome projects. The main goal of protein separation methods is to detect differentially expressed proteins across treatment groups. However, a major bottleneck toward that goal is the misalignment of gels due to warping and thus confounding biological variation with non-biologically relevant distortions. This paper provides a computationally feasible gel alignment methods based on powerful optimization techniques such as interior point methods. With 2D-PAGE technique, proteins are separated orthogonally according to their charge and size. The separated proteins are then stained so that they are readily detectable, and the gels are digitally scanned into a database for storage. Gel images are

It is shown that, in comparison to the results obtained from a conventional least squares approach, a total least squares solution leads to significant improvements in the geometry and appearance of images synthesised in a linear combination of views procedure. Use of the total least squares criterion is appropriate when errors on the control points are independently and identically distributed between the basis images and the target image being synthesised. When this is not be the case it is pointed out that the generalised total least squares procedure should be used. A synthetic object is used to evaluate the improvement in geometric accuracy obtained by use of the total least squares solution in comparison to a classical least squares method. Simulated and real images of laboratory test objects are similarly used to illustrate the improvement in appearance of images reconstructed by means of the total least squares procedure.