LK法-AnIterativeImageRegistrationTechnique.docx

LK法
An Iterative Image Registration Technique
with an Application to Stereo Vision
立体视觉应用上的迭代图像配准技术
Abstract
Image registration finds a variety of applications puter 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. 图像配准找到了在计算机视觉中的多种应用。不幸的是,传统的图像配准技术花费较大。我们采用了一个新的图像配准技术,它使用了图像的空间强度梯度,通过用Newton-Raphson迭代来找到一个好的匹配。我们的技术速度更快,因为它比现存的技术检验了更少的图像之间的潜在匹配。此外,这个配准技术可以普遍化到处理旋转、缩放和剪切。我们展示了我们的技术能适用于立体视觉系统。
1. Introduction简介
Image registration finds a variety of applications puter vision, such as image matching for stereo vision, pattern recognition, and motion analysis. Unfortunately, existing techniques for image registration tend to be costly. Moreover, they generally fail to deal with rotation or other
distortions of the ,如立体视觉的图像匹配、模式识别和运动分析。不幸的是,现存的用于图像匹配的技术花费过高。此外,它们大多不能处理图像的旋绕或其他扭曲。
In this paper we present a new image registration technique that uses spatial intensity gradient information to direct the search for the position that yields the best ,我们展示了一个新的图像配准技术,它运用了空间强度梯度信息来指导对位置的研究,这可以得到最佳匹配。By taking more information about the images into account, this technique is able to find the best match between two images with far parisons of images than techniques which examine the possible positions of registration in some fixed ,我们的技术将图像中更多的信息考虑进来,从而用了更少的图像之间的比对就可以找到两幅图之间的最佳匹配。Our technique takes advantage of the fact that in many applications the two images are already in approximate registration. This technique