Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton-Raphson iteration. Our technique is faster because it examines far fewer potential matches between the images than existing techniques. Furthermore, this registration technique can be generalized to handle rotation, scaling and shearing. We show show our technique can be adapted for use in a stereo vision system. 1. Introduction Image registration finds a variety of applications in computer vision, such as image matching for stereo vision, pattern recognition, and motion analysis. Untortunately, existing techniques for image registration tend to be costly. Moreover, they generally fail to deal with rotation or other distortions of the images. In this paper we present a new image registratio...

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.

Although it is well known that cross correlation can be efficiently implemented in the transform domain, the normalized form of cross correlation preferred for feature matching applications does not have a simple frequency domain expression. Normalized cross correlation has been computed in the spatial domain for this reason. This short paper shows that unnormalized cross correlation can be efficiently normalized using precomputing integrals of the image and image 2 over the search window. 1

Two commonly used approaches for building a virtual reality (VR) world are the model-based approach and the image-based approach. Recently, the image-based approach has received much attention for its advantages of being easier to build a VR model and of being able to provide photo-realistic views. However, traditional image-based VR systems can not produce the stereo views that can give the users the feeling of 3D depth. In this paper, we present a panoramic stereo imaging (PSI) system which can produce stereo panoramas for image-based VR systems. This PSI system is referred to as the PSI-II system, which is an improved system of our previous experimental PSI-I system. The PSI-I system uses a well-calibrated tripod system to acquire a series of stereo image pairs, while the PSI-II system does not require the use of a well-calibrated tripod system and can automatically generate a stereo-pair of panoramic images by using a novel disparity warping technique and a hierarchical se...

Stereo matching is important in the area of computer vision and photogrammetry. This paper presents a fast stereo matching algorithm which produces a dense disparity map by using a pyramid structure, fast correlation and dynamic programming techniques. Fast correlation is achieved by using the box filtering technique which is invariant to the size of the correlation window. The disparity for each scan line is found in the correlation matrix by finding the best path using dynamic programming rather than simply choosing the position that gives the maximum correlation coefficient. Both synthetic and real image tests have been performed, and good results have been obtained. Keywords: Image matching, Stereo vision, Pyramid, Coarse-to-fine, Fast correlation, Dynamic programming, Box filtering, Similarity measure. 1 Introduction The correspondence problem in stereo vision concerns the matching of points or other kinds of primitives in two images such that the matched points are the project...

Although laser retinal surgery is the best available treatment for choridal neovascularization, the current procedure has a low success rate (50%). Challenges, such as motioncompensated beam steering, ensuring complete coverage and minimizing incidental photodamage, can be overcome with improved instrumentation. This paper presents core image processing algorithms for 1) rapid identification of branching and crossover points of the retinal vasculature; 2) automatic montaging of video retinal angiograms; 3) real-time location determination and tracking using a combination of feature-tagged point-matching and dynamic-pixel templates. These algorithms tradeoff conflicting needs for accuracy, robustness to image variations (due to movements and the difficulty of providing steady illumination) and noise, and operational speed in the context of available hardware. The algorithm for locating vasculature landmarks performed robustly at a speed of 16--30 video image frames/s depending upon the field on a Silicon Graphics workstation. The montaging algorithm performed at a speed of 1.6--4 s for merging 5--12 frames. The tracking algorithm was validated by manually locating six landmark points on an image sequence with 180 frames, demonstrating a mean-squared error of 1.35 pixels. It successfully detected and rejected instances when the image dimmed, faded, lost contrast, or lost focus.

In 1972, Barnea and Silverman presented a new approach to the wide field of template matching, the SSD--algorithm. Further work has been done to adapt the method to gain subpixel accuracy. Intense investigation of the proposed algorithms led to our new approach: by interpolating the template instead of the reference image, and by applying sort of an error--correction to the resulting subpixel--value, both computation time and accuracy can be improved. Exhaustive experiments with a CCD--camera and various kinds of reference images showed that a maximum error of 10% of the pixel period can be expected. Depending on the kind of image, mean square errors range from 0.4% to 4%. INTRODUCTION In 1972, Barnea and Silverman presented the SSD--algorithm, a fast way to solve the problem of image registration [1]. Extending it to subpixel accuracy ([2],[3]), nevertheless, increased the computational cost to an amount where real--time applications seemed almost impossible. In this paper we presen...

Abstract—Digital subtraction angiography (DSA) is a well-established modality for the visualization of blood vessels in the human body. A serious disadvantage of this technique, inherent to the subtraction operation, is its sensitivity to patient motion. The resulting artifacts frequently reduce the diagnostic value of the images. Over the past two decades, many solutions to this problem have been put forward. In this paper, we give an overview of the possible types of motion artifacts and the techniques that have been proposed to avoid them. The main purpose of this paper is to provide a detailed review and discussion of retrospective motion correction techniques that have been described in the literature, to summarize the conclusions that can be drawn from these studies, and to provide suggestions for future research. Keywords—Digital subtraction angiography, motion correction, registration, matching. Abbreviations

Abstract-Registration of retinal images taken at different times frequently is required to measure changes caused by disease or to document retinal location of visual stimuli. Cross-correlation has been used previously for such registration, but it is computationally intensive. We have modified a faster algorithm, sequential similarity detection (SSD), to use only the portion of the template that contains retinal vessels. When compared to standard SSD and cross-correlation, this modification improves the reliability of detection for a variety of retinal imaging modalities. The improved reliability enables implementation of a two-stage registration strategy that further decreases the amount of computation and increases the speed of registration. I.

In this paper, some image registration algorithms are investigated for the purpose of image fusion in a digital camera application. A hybrid scheme which uses both feature-based and intensity-based methods is proposed. In particular, an edge-based image registration approach is developed to guide the intensity-based registration which uses optical flow estimation. The idea of coarse-to-fine multi-scale iterative refinement is also utilized. The combination of these different methods tends to compensate for any deficiencies in the individual methods. Experiments show that our approach provides accurate registrations for the digital camera application. It is also demonstrated that the approach proves useful for registering some multi-spectral images. Keywords-Image fusion, registration, multi-scale, optical flow, feature-based. Tel. 610-758-4909, email: zhz3@lehigh.edu y Tel. 610-758-3459, FAX: 610-758-6279, email: rblum@eecs.lehigh.edu (contact author) z This research was supporte...