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。     

Stereo rectification of pushbroom satellite images by robustly estimating the fundamental matrix

ABSTRACT

Stereo rectification is one of the most important steps for stereo matching and subsequently for digital surface model generation from satellite stereo images. This study proposes a new framework to rectify two pushbroom images along the epipolar geometry in order to omit the vertical parallax between two images. Here, we assume the interior and relative parameters between the two pushbroom images are not known and the images can be taken at different dates. Traditional stereo rectification methods of pushbroom images require metadata such as rational polynomial coefficients (RPCs), parameters of physical sensor model or ground control points (GCPs). In this study, we develop an image-based framework for stereo rectification, which works without the need for such data. In the proposed framework, the correspondences are densely extracted by a tilling strategy, and then the fundamental matrix is robustly estimated by two geometric constraints. Both affine and projective fundamental matrices could be used for stereo rectification from pushbroom stereo images. The results on IRS P5, World view III, GeoEye and IKONOS stereo pairs as well as on multi-date stereo images demonstrate that the pushbroom images are rectified with sub-pixel accuracy.     

三视校正的理论及鲁棒性算法

主要讨论两方面的工作.首先,对三视校正问题进行理论分析,给出了校正后图像的基本矩阵与其约束条件之间的关系,讨论了三视校正过程中的6个自由参数的几何含义.这些结果为处理校正过程中带来的图像射影畸变提供了理论根据.其次,在RANSAC(random sampling consensus)框架下,提出了一种鲁棒的三视校正算法.与传统的校正算法不同,该算法不再只依赖于基本矩阵,而是直接利用了原始匹配点的信息.这种基于点的方法有两个优点:一方面,由于噪声的干扰,基本矩阵往往估计得不够准确;另一方面,由于基本矩阵的评价准则与校正结果的评价准则不同,即使从好的基本矩阵出发,也未必能获得好的校正结果.大量的模拟和真实图像实验表明,该算法具有很强的抗噪声及抗错误匹配的能力,能够获得令人满意的校正效果.     

海面透视图像的度量矫正方法

在海洋测绘中,通过图像矫正的方法估算出测量仪器的位置具有非常重要的意义。针对海面目标位置估算中的图像透视矫正问题,提出一种基于平面虚圆点图像的海面图像度量矫正方法。利用不同角度下照片中圆形特征物的图像计算出绝对二次曲线的图像;根据绝对二次曲线以及图像中的海平线辨认海平面虚圆点的图像;通过对与海平面虚圆点对偶的二次曲线的图像进行奇异值分解,获得海平面图像的度量矫正矩阵。在图像实验中,平面上的角度矫正误差小于1.3°,表明这种方法具有较好的矫正精度,能够满足多种海洋测绘作业的要求。     

基于点特征的多源遥感影像高精度自动配准方法

提出了一种基于点特征的多源遥感影像高精度自动配准方法。该方法采用了由粗到精的配准策略。首先利用SIFT算子和一次多项式实现影像的粗配准,粗配准后的影像和参考影像将处于同一尺度（像素采样间隔）和参考坐标系下。其次在粗配准后的影像上提取分布均匀的特征点,根据前一步得到的影像间的坐标关系,在参考影像上确定一个较小的搜索范围,使用相关系数匹配出同名点,同时用Baarda数据探测法剔除粗差。最后根据同名点构建三角网对影像进行精配准。实验结果表明:该方法能够实现多源遥感影像的高精度配准。     

宽基线视差图像的拼接算法

针对两幅视差图像的拼接问题,提出了一种新算法,即利用Hessian仿射不变检测算子检测出特征区域,利用SIFT特征描述算子提取特征区域特征矢量,根据特征矢量的欧几里德距离来建立图像间的稀疏对应关系;由这些对应点稀疏地确定场景中的一些点,以这些点为顶点建立场景的三角面片近似,再据此将重叠区域重投影生成推扫式成像的中间部分图像。将中间部分推扫式成像图像和原左图像的左半部分以及原右图像的右半部分一起拼接生成大图像。利用实际图像进行的拼接实验表明该算法是一个有效的视差图像拼接算法。     

Efficient extraction of metric measurements for planar scene under 2D homography with the help of planar circles

Extraction of metric properties from perspective view is a challenging task in many machine vision applications. Most conventional approaches typically first recover the perspective transformation parameters up to a similarity transform and make measurements in the resulting rectified image. In this paper, a new approach is proposed to allow quick and reliable Euclidean measures to be made directly from a perspective view without explicitly recovering the world plane. Unlike previous planar rectification strategies, our approach makes use of planar circles to help identify the image of the absolute conic, which makes it capable of performing effective rectification under many difficult cases that are unable to be treated with other rectification approaches. This is made possible by solving the images of the circular points in closed-form from the vanishing line and the image of one arbitrary planar circle and by exploiting the invariant relationship between the circular points and the absolute conic under projective transformation. Subsequently, planar Euclidean measures can be made directly from the image plane. The practical advantages and the efficiency of this method are demonstrated by experiments on both synthetic and real scenes.     

Stereo by intra- and inter-scanline search using dynamic programming

This paper presents a stereo matching algorithm using the dynamic programming technique. The stereo matching problem, that is, obtaining a correspondence between right and left images, can be cast as a search problem. When a pair of stereo images is rectified, pairs of corresponding points can be searched for within the same scanlines. We call this search intra-scanline search. This intra-scanline search can be treated as the problem of finding a matching path on a two-dimensional (2D) search plane whose axes are the right and left scanlines. Vertically connected edges in the images provide consistency constraints across the 2D search planes. Inter-scanline search in a three-dimensional (3D) search space, which is a stack of the 2D search planes, is needed to utilize this constraint. Our stereo matching algorithm uses edge-delimited intervals as elements to be matched, and employs the above mentioned two searches: one is inter-scanline search for possible correspondences of connected edges in right and left images and the other is intra-scanline search for correspondences of edge-delimited intervals on each scanline pair. Dynamic programming is used for both searches which proceed simultaneously: the former supplies the consistency constraint to the latter while the latter supplies the matching score to the former. An interval-based similarity metric is used to compute the score. The algorithm has been tested with different types of images including urban aerial images, synthesized images, and block scenes, and its computational requirement has been discussed.     

Towards reliable matching of images containing repetitive patterns

This paper aims to solve the problem of matching images containing repetitive patterns. Although repetitive patterns widely exist in real world images, these images are difficult to be matched due to local ambiguities even if the viewpoint changes are not very large. It is still an open and challenging problem. To solve the problem, this paper proposes to match pairs of interest points and then obtain point correspondences from the matched pairs of interest points based on the low distortion constraint, which is meant that the distortions of point groups should be small across images. By matching pairs of interest points, local ambiguities induced by repetitive patterns can be reduced to some extent since information in a much larger region is used. Meanwhile, owing to our newly defined compatibility measure between one correspondence and a set of point correspondences, the obtained point correspondences are very reliable. Experiments have demonstrated the effectiveness of our method and its superiority to the existing methods.     

Planar Motion Estimation and Linear Ground Plane Rectification using an Uncalibrated Generic Camera

We address and solve the self-calibration of a generic camera that performs planar motion while viewing (part of) a ground plane. Concretely, assuming initial sets of correspondences between several images of the ground plane as known, we are interested in determining both the camera motion and the geometry of the ground plane. The latter is obtained through the rectification of the image of the ground plane, which gives a bijective correspondence between pixels and points on the ground plane.     

基于匹配与平差的景象镶嵌方法

在概括介绍消附相邻景象辐射差异常用算法的基础上,为有效消除相邻景象间几何位置的差异,提出了一种将影象匹配与平差理论相结合的影象镶嵌新算法,该方法是在镶嵌影象的重叠部分进行基于特征的影象匹配,即首先获取一序列同名点,且这些同名点的匹配精度在一个象元以内;然后用正形多项式模拟这些同名点间的几何位置差异,再按最小二乘法原理对右边影象进行平差改正,以实现两影象空间位置上的无缝连接。实验结果表明,庐镶嵌方法具有良好的效果。     

Robust uncalibrated stereo rectification with constrained geometric distortions (USR-CGD)

A novel algorithm for uncalibrated stereo image-pair rectification under the constraint of geometric distortion, called USR-CGD, is presented in this work. Although it is straightforward to define a rectifying transformation (or homography) given the epipolar geometry, many existing algorithms have unwanted geometric distortions as a side effect. To obtain rectified images with reduced geometric distortions while maintaining a small rectification error, we parameterize the homography by considering the influence of various kinds of geometric distortions. Next, we define several geometric measures and incorporate them into a new cost function as regularization terms for parameter optimization. Finally, we propose a constrained adaptive optimization scheme to allow a balanced performance between the rectification error and the geometric error. Extensive experimental results are provided to demonstrate the superb performance of the proposed USR-CGD method, which outperforms existing algorithms by a significant margin.     

一种图像校正重采样效应的评估及优化方法

分析了图像校正中重采样效应的主要表现形式，建立了一种重采样效应的评估方法．在此基础上，根据图像投影变换及校正图像上基础矩阵的性质，给出了两种类型的图像校正不变量，提出了一种独立于图像校正过程的重采样效应优化方法，通过投影区域修正的方法提高校正图像质量，实验证明，该方法能够有效的降低图像变形，减少图像分辨率的损失．     

Efficient Video Rectification and Stabilisation for Cell-Phones

This article presents a method for rectifying and stabilising video from cell-phones with rolling shutter (RS) cameras. Due to size constraints, cell-phone cameras have constant, or near constant focal length, making them an ideal application for calibrated projective geometry. In contrast to previous RS rectification attempts that model distortions in the image plane, we model the 3D rotation of the camera. We parameterise the camera rotation as a continuous curve, with knots distributed across a short frame interval. Curve parameters are found using non-linear least squares over inter-frame correspondences from a KLT tracker. By smoothing a sequence of reference rotations from the estimated curve, we can at a small extra cost, obtain a high-quality image stabilisation. Using synthetic RS sequences with associated ground-truth, we demonstrate that our rectification improves over two other methods. We also compare our video stabilisation with the methods in iMovie and Deshaker.     

基于仿射点对应的分层重构

提出了一种基于仿射点对应的分层重构方法,所谓仿射点对应是指相差一个仿射变换的两个空间点集的图像对应．该方法主要分为以下三个步骤：首先,从点对应计算准仿射重构;然后,由仿射点对应的准仿射重构建立一个三维射影变换,并利用这个射影变换的特征向量来确定无穷远平面,从而得到仿射重构;最后,从仿射重构所获得的无穷远平面单应矩阵标定摄像机内参数,进而得到度量重构．在上述三个步骤中,第二个步骤是最关键的,即如何确定对应于无穷远平面的特征向量,这也是该文的新思想和主要贡献所在．仿真和真实图像实验均表明,该文的方法是有效的,并且有很好的鲁棒性．     

利用图像校正的快速目标识别算法

提出了一种基于图像校正的快速目标识别算法,特别适合于航拍照片中地面上面目标的识别。算法可以使目标模型单一化,在很大程度上克服了目标识别模型复杂、数据运算量大、计算实时性差等缺点,提高了目标识别的实时性和精确性。首先对图像进行感兴趣区域的检测;对检测出的区域进行图像的正视校正;然后对校正后的区域进行特征提取;最后进行目标识别,并输出目标信息,完成识别过程。实验表明,该算法用于大倾角航片目标识别是有发展潜力和前途的。     

Rectified catadioptric stereo sensors

It has been shown elsewhere how mirrors can be used to capture stereo images with a single camera, an approach termed catadioptric stereo. We present novel catadioptric sensors that use mirrors to produce rectified stereo images. The scanline correspondence of these images benefits real-time stereo by avoiding the computational cost and image degradation due to resampling when rectification is performed after image capture. First, we develop a theory which determines the number of mirrors that must be used and the constraints on those mirrors that must be satisfied to obtain rectified stereo images with a single camera. Then, we discuss in detail the use of both one and three mirrors. In addition, we show how the mirrors should be placed in order to minimize sensor size for a given baseline, an important design consideration. In order to understand the feasibility of building these sensors, we analyze rectification errors due to misplacement of the camera with respect to the mirrors     

Digital orthophotography: mapping with pictures

Aerial photographs and maps would seem a natural combination to record and analyze geographical information: maps provide geometric information and photographs add realistic, timely detail. But cameras record images on a flat plane, whereas the earth is curved and its terrain takes on many varied shapes-all of which distort the image geometry and render it invalid for mapping and geographic analysis. Digital orthophotographs solve this problem. A digital orthophoto starts with a rasterized (scanned) aerial photograph; a process called rectification (described below) removes distortions arising from the camera lens, the aircraft's position, and elevation and other topographical features. This transforms aerial photos into high-resolution digital images that correctly represent the geometry of an area and its terrain. These images can be used as standard true-scale representations of geographic sectors-a function already served by analog orthophotos, which must be painstakingly scanned and rectified in small strips or patches. Their fully digital format makes digital orthophotos useful as base maps in geographical information systems (GIS) used for creating and revising topographic and planimetric maps, vegetation and timber management, environmental impact assessments, and infrastructure assessment     

Accelerated Backward Warping

In this paper a plane-based backward warping algorithm is proposed to generate novel viwews from multiple reference images.First.depth information is employed to reconstruct space planes from individual refernce images and calculate the potential occluding relationship between these planes.Then the planes which represent each identical space plane from different reference images are compared with each other to decide the one with the best sample rate to be preserved and used in the later warping period while the other samples are abandoned.While the image of a novel view is produced,traditional methods in computer graphics,such as visibility test.and clipping,are used to process the planes reconstructed.Then the planes processed are projected onto the desired image form the knowledge on which plane the desired image pixels are warped from can be acquired.Finally,pixels‘ depth of the desired image is calculated and then a ackwared warping is performed from these pixels to the reference images to obtain their colors.The storage requirement in the algorithm is small and increases slowly with the number of reference images increases.By combining the strategy of only preserving the best sample parts and the backward warping algorithm ,the sample problem could be well tackled.     

Skeleton-based image warping

Image warping refers to the 2D resampling of a source image onto a target image. Despite the variety of techniques proposed, a large class of image warping problems remains inadequately solved: mapping between two images which are delimited by arbitrary, closed, planar curves, e.g., handdrawn curves. This paper describes a novel algorithm to perform image warping among arbitrary planar shapes whose boundary correspondences are known. A generalized polar coordinate parameterization is introduced to facilitate an efficient mapping procedure. Images are treated as collections of interior layers, extracted via a thinning process. Mapping these layers between the source and target images generates the 2D resampling grid that defines the warping. The thinning operation extends the standard polar coordinate representation to deal with arbitrary shapes.