基于鲁棒方法的图像整合技术

本文讨论了基于圆序列的整合图像问题．由于相机旋转拍摄图片，可避免光源变化、遮挡和 外观变化等出现在一般匹配中的问题, 因此自动生成匹配点要容易得多．我们采用一种鲁棒 的方法，只要输入少量点，就可以自动寻找匹配点对并对投影变换进行求解．整合参数的变 化，可得到不同视点下的整合图像．该方法不需要事先知道摄象机的内、外参数．     

基于灭点的径向畸变自动校正方法

镜头畸变影响着三维重建、几何量测等工作的质量。本文根据图像中的灭点几何约束条件,提出一种基于灭点的弱径向畸变自动校正方法。为避免包含畸变中心参数的非线性模型优化结果的不稳定性,本文在求解径向畸变系数之后进一步对畸变中心进行优化。首先根据灭点几何约束条件建立关于灭点与径向畸变系数的非线性模型,使用LM算法估计灭点坐标与径向畸变参数,然后根据质量评价准则对畸变中心和径向畸变系数进一步迭代优化;最后,通过真实图像对该方法的可行性进行分析验证。本文充分利用图像中的灭点属性,提出一种新的镜头径向畸变校正方法。实验结果表明,该方法能够有效的对径向畸变进行校正,并克服了传统校正方法的不稳定性。     

由灭点进行径向畸变的自动校正

目的镜头畸变影响着3维重建、几何量测等工作的质量。根据图像中的灭点几何约束条件,提出一种根据灭点进行弱径向畸变自动校正方法。方法为避免包含畸变中心参数的非线性模型优化结果的不稳定性,在求解径向畸变系数之后进一步对畸变中心进行优化。首先根据灭点几何约束条件建立关于灭点与径向畸变系数的非线性模型,使用Levenberg-Marquardt(LM)算法估计灭点坐标与径向畸变参数,然后根据质量评价准则对畸变中心和径向畸变系数进一步迭代优化;最后,通过真实图像对该方法的可行性进行分析验证。结果采用不同的数据对径向畸变进行了有效地校正,并采用校正后的数据进行了相机标定,标定结果相对于传统基于非量测校正方法有明显的提高。结论充分利用图像中的灭点属性,提出一种新的镜头径向畸变校正方法。实验结果表明,该方法能够有效地对径向畸变进行校正,并克服了传统基于非量测畸变校正方法的不稳定性。     

考虑径向畸变的机器人视觉系统的参数标定

针对GRB-400机器人视觉系统,建立完整的摄像机一阶径向畸变模型。用GRB系统的Matrox图像采集卡采集标定点坐标,利用径向排列约束方法 (简称RAC)建立线性方程组求解摄像机的径向畸变参数。基于此畸变参数实现图像校正,以提高对目标物体的定位精度,从而提高机器人视觉系统对摄像机标定参数变化的鲁棒性。实验结果表明,该方法有较高的标定精度。     

基于改进的SUSAN法的摄像机线性标定方法

设计并实现了一种考虑径向畸变的逐步线性摄像机标定方法。结合边缘检测，缩小了SUSAN法检测角点的范围，并利用角点的邻域特征，剔除伪角点，从而提高了SUSAN法角点检测的速度和准确度。利用此改进的SUSAN法精确提取方格模板角点的亚像素坐标，并通过预标定获得主点坐标；然后在考虑摄像机径向畸变的情况下建立摄像机模型，并求解摄像机内外参数。最后通过实验及误差分析表明，本标定方法具有较高的精度和较好的实时性。     

基于基本矩阵的相机畸变差校正方法研究

在计算机视觉的应用领域中,为了提高图像量测和三维重建的精度,必须对相机的畸变误差进行修正.本文提出了一种基于基本矩阵的相机径向畸变的自动校正方法,该方法不需要预先获得场景的结构信息和相机的内部参数,仅利用两张影像同名点集之间的内在几何关系,即可求取相机的径向畸变系数,进而可对这两幅图像的畸变误差进行自动校正.实验结果表明,该方法是一种有效的畸变图像校正算法,能够获得到满意的校正结果.     

面向增强视频的基于结构和运动恢复的摄像机定标

提出了一种高效鲁棒的长序列摄像机定标算法，能稳定处理焦距未知且变化的视频序列，适用于增强视频的应用．该算法从长视频序列中根据特征匹配点提炼出相互之间具有较长基线的关键帧，以保证求解的稳定性．算法先在关键帧序列上渐进式求解，以准确恢复特征匹配点的互维结构信息；利用精确恢复的三维点，求解整个序列的摄像机运动参数．该算法选择最适合初始化的三帧求解，并将解及时从射影空间转换到欧氏空间．实验结果显示了所恢复的摄像机参数和三维点的高度精确性，证明了该方法稳定高效，能够满足增强视频的高端要求．     

一种摄像机亚象素线性标定方法

提出了一种考虑径向畸变的摄像机线性标定方法。采用一个方格图样模板进行标定,先利用改进的Harris算子精确提取角点的亚象素坐标,通过预标定获得主点坐标;然后在考虑摄像机径向畸变的情况下建立摄像机模型,并求解摄像机内外参数。实验及误差分析表明:该标定方法具有较高的精度和较好的实时性。     

一种基于基本矩阵的相机畸变差自动校正方法

在计算机视觉的应用领域中,为了提高图像量测和3维重建的精度,必须对相机的畸变误差进行修正。为此提出了一种基于基本矩阵的相机径向畸变的自动校正方法,该方法不需要预先获得场景的结构信息和相机的内部参数,仅利用两张影像同名点集之间的内在几何关系,即可求取相机的径向畸变系数,进而可对这两幅图像的畸变误差进行自动校正。试验结果表明,该方法是一种有效的畸变图像校正算法,能够获得到满意的校正结果。     

卫星影像仿射畸变的自动校正方法

针对卫星影像存在的仿射畸变，研究并给出了一种实用的自动校正疗法。分析了仿射畸变模型参数的计算方法，对几何校正控制点进行了自动选定，辨识出了畸变模型参数，采用均值法及中值法对模型辨识参数进行优化处理，进而通过坐标变换及灰度的双线性插值实现卫星影像仿射畸变的自动、精确校正。仿真实验结果说明了该方法的可行性、有效性。     

鱼眼图像径向畸变校正的一种新方法

由于鱼眼相机视场广阔在很多领域都得到了广泛应用,但其图像存在着明显的径向 畸变,需要在应用之前加以校正。为此分析了径向畸变模型解析解的非唯一性;根据径向畸变的 对称性,得出了畸变直线与理想直线之间的关系,即畸变校正的解析表达式;提出了一种鱼眼图 像径向畸变校正的新方法。实验证明,该方法计算简单,能有效校正包含直线特征的场景。     

Fast and robust numerical solutions to minimal problems for cameras with radial distortion

A number of minimal problems of structure from motion for cameras with radial distortion have recently been studied and solved in some cases. These problems are known to be numerically very challenging and in several cases there were no practical algorithms yielding solutions in floating point arithmetic. We make some crucial observations concerning the floating point implementation of Gröbner basis computations and use these new insights to formulate fast and stable algorithms for two minimal problems with radial distortion previously solved in exact rational arithmetic only: (i) simultaneous estimation of essential matrix and a common radial distortion parameter for two partially calibrated views and six image point correspondences and (ii) estimation of fundamental matrix and two different radial distortion parameters for two uncalibrated views and nine image point correspondences. We demonstrate that these two problems can be efficiently solved in floating point arithmetic in simulated and real experiments. For comparison we have also invented a new non-minimal algorithm for estimating fundamental matrix and two different radial distortion parameters for two uncalibrated views and twelve image point correspondences based on a generalized eigenvalue problem.     

A Simple Method of Radial Distortion Correction with Centre of Distortion Estimation

This paper presents a new simple method to determine the distortion function of camera systems suffering from radial lens distortion. Neither information about the intrinsic camera parameters nor 3D-point correspondences are required. It is based on single image and uses the constraint, that straight lines in the 3D world project to circular arcs in the image plane, under the single parameter Division Model. Most of former approaches to correct the radial distortion are based on the collinearity of undistorted points. The proposed method in this paper, however, is based on the conclusion that distorted points are concyclic and uses directly the distorted points not undistorted points, therefore it should be more robust. It also computes the centre of radial distortion, which is important in obtaining optimal results. The results of experimental measurements on synthetic and real data are presented and discussed.

Parameter-free radial distortion correction with center of distortion estimation

We propose a method of simultaneously calibrating the radial distortion function of a camera and the other internal calibration parameters. The method relies on the use of a planar (or, alternatively, nonplanar) calibration grid which is captured in several images. In this way, the determination of the radial distortion is an easy add-on to the popular calibration method proposed by Zhang [24]. The method is entirely noniterative and, hence, is extremely rapid and immune to the problem of local minima. Our method determines the radial distortion in a parameter-free way, not relying on any particular radial distortion model. This makes it applicable to a large range of cameras from narrow-angle to fish-eye lenses. The method also computes the center of radial distortion, which, we argue, is important in obtaining optimal results. Experiments show that this point may be significantly displaced from the center of the image or the principal point of the camera.     

A unifying geometric representation for central projection systems

In this paper, we study projection systems with a single effective viewpoint, including combinations of mirrors and lenses (catadioptric) as well as just lenses with or without radial distortion (dioptric systems). First, we extend a well-known unifying model for central catadioptric systems to incorporate a class of dioptric systems with radial distortion. Second, we provide a new representation for the image plane of central systems. This representation is the lifting through a Veronese map of the original image plane to the 5D projective space. We study how a collineation in the original image plane can be transferred to a collineation in the lifted space, and we prove that in the case of central parabolic systems and cameras with lens distortion the locus of the lifted points representing projections of world lines is a plane. The similarities between paracatadioptric systems and lens with radial distortion are emphasized by extending to the latter algorithms initially established for the former.     

高阶径向畸变对张正友平面标定算法精度的影响

机标定是视觉测量工作中非常重要的一步。张正友教授提出的基于平面标定物的相机标定方法,是目前使用最广泛的方法之一。但张氏方法只考虑前两阶的径向畸变,因此,本文研究高阶径向畸变对张氏标定方法精度的影响。以棋盘格作为仿真模板,对其进行基于Matlab的仿真标定实验,求得不同径向畸变条件下标定结果的误差,并分析其关系。通过仿真实验结果分别绘制三阶径向畸变与标定误差的关系曲线及四阶径向畸变与标定误差的关系曲线。三阶径向畸变和四阶径向畸变对标定误差的影响十分相似,高阶径向畸变与标定误差关系曲线基本符合抛物线。同时,高阶径向畸变对二阶径向系数标定精度的影响远大于对一阶径向系数标定精度的影响。