基于网格图像自动检测的镜头畸变校正*

针对广角镜头所采集图像存在的畸变问题,提出了一种基于模板匹配和质心检测的高精度控制点检测法,并采用基于除法模型和正交相干相位检测法对畸变网格图像进行了高精度校正。实验结果表明,该镜头畸变校正算法能克服光照等不定因素,对畸变的网格图像交叉控制点进行高精度自动提取,并自动计算畸变图像中每一点的校正参数,实现了镜头畸变的高精度、全自动校正。     

A new approach for nonlinear distortion correction in endoscopicimages based on least squares estimation

Images captured with a typical endoscope show spatial distortion, which necessitates distortion correction for subsequent analysis. In this paper, a new methodology based on least squares estimation is proposed to correct the nonlinear distortion in the endoscopic images. A mathematical model based on polynomial mapping is used to map the images from distorted image space onto the corrected image space. The model parameters include the polynomial coefficients, distortion center, and corrected center. The proposed method utilizes a line search approach of global convergence for the iterative procedure to obtain the optimum expansion coefficients. A new technique to find the distortion center of the image based on curvature criterion is presented. A dual-step approach comprising token matching and integrated neighborhood search is also proposed for accurate extraction of the centers of the dots contained in a rectangular grid, used for the model parameter estimation. The model parameters were verified with different grid patterns. The distortion-correction model is applied to several gastrointestinal images and the results are presented. The proposed technique provides high-speed response and forms a key step toward online camera calibration, which is required for accurate quantitative analysis of the images.     

基于Hough变换的摄像机畸变非量测标定方法

广角镜头在获得大视场的同时也引入了严重的光 学畸变,必须对从广角相机所获得的图像进行畸变校正。本文首先 提取图像中的曲线,依据在单参数除式畸变模型下直线段畸变成像近似呈圆弧的特点,在圆 弧拟合过程中标定出畸变参数与 畸变中心的初始近似值;进而采用一种在Hough变换空间中使 用熵函数估计校正后曲线直线度的方 法,利用熵函数对初始近似值作进一步的优化,最终求取更加精确的畸变参数与畸变中心 。基于工程实例,分别利用圆 弧拟合求初始值方法与本文所提出方法对目标图像进行畸变校正。仿真和真实图像实验表明 ,本文方法仅利用单幅图像即可实 现高精度的标定系数,且方法具有较高的稳定性,操作简单、方便和易于实现。     

MEMS振镜扫描共聚焦图像畸变机理分析及校正

在皮肤反射式共聚焦显微成像过程中，针对MEMS振镜二维扫描引起的共聚焦图像畸变，开展了光束偏转理论分析，得出了投影面扫描图像的具体形状表征，理论畸变图像与真实畸变图像一致，明确了畸变机理，提出一种有效的畸变校正算法，实现对图像二维畸变的校正。首先记录原始光栅畸变图像，然后基于Hessian矩阵提取光栅中心线，拾取特征点并设置基准参考线，通过基于最小二乘法的7次多项式插值法标定二维方向像素畸变校正量，采用加权平均法填补间隙像素灰度值，最终实现图像畸变校正。利用网格畸变测试靶实验得出7次多项式插值后的校正决定系数最高、均方根误差值最低，整幅512行图像在7次多项式插值后最优行数占379行，比例为74%，通过残差分析，二维方向上残差最大为4个像素，最小为0个像素，平均为1.15个像素，校正结果较为精确。皮肤在体实时成像实验显示，图像畸变校正后组织结构特征更加真实准确，表明这种校正算法有效可行，有助于皮肤疾病的准确诊断。     

利用图像畸变对称性实现相机中心位置标定

分析了图像的畸变特征,提出一种新的相机中心标定的方法.在提出的四点假设前提下,认为图像畸变有中心对称的特点.采用高斯曲线拟合有畸变的直线,多条平行直线的畸变拟合高斯曲线的顶点连线将经过图像中心.通过对多簇不平行直线的畸变曲线拟合,可获得多条过图像中心的直线,联合求解得到图像的中心位置.这种直接获得图像中心的方法,无须已知任何外部参数,算法简单且计算复杂度低,结果的稳定性好,在实验中取得良好的效果.     

弹载SAR图像几何失真校正误差分析

该文主要讨论了弹载侧视合成孔径雷达(SAR)在导弹下降飞行过程中所获取图像的几何失真校正及其误差分析问题。由于要求成像的过程中,弹体的高度在不断减小,SAR图像存在严重的几何失真,该文根据成像过程中的几何关系,说明了采用子孔径RD算法获得的SAR图像几何失真的校正方法,着重对校正后图像的几何失真误差进行了分析,通过成像处理仿真试验验证了几何校正方法以及误差分析的正确性。     

内窥镜图像畸变校正的新方法

本文提出了基于全局收敛线性搜索的内窥镜图像桶形畸变的校正方法。方法假定畸变为圆对称形式,并利用多项式映射将畸变图像从畸变图像空间映射到校正图像空间。根据内窥镜成像特性以及基于全局收敛的线性搜索法来确定畸变图像中心和多项式系数。采用非线性回归对校正图像进行补偿。试验结果证实,该方法校正效果好、响应速度快、满足需要定量分析的图像处理的要求。     

Unsupervised fisheye image correction through bidirectional loss with geometric prior

Neural network based methods for fisheye distortion correction are effective and increasingly popular, although training network require a high amount of labeled data. In this paper, we propose an unsupervised fisheye correction network to address the aforementioned issue. During the training process, the predicted parameters are employed to correct strong distortion that exists in the fisheye image and synthesize the corresponding distortion using the original distortion-free image. Thus, the network is constrained with bidirectional loss to obtain more accurate distortion parameters. We calculate the two losses at the image level as opposed to directly minimizing the difference between the predicted and ground truth of distortion parameters. Additionally, we leverage the geometric prior that the distortion distribution depends on the geometric regions of fisheye images and the straight line should be straight in the corrected images. The network focuses more on the geometric prior regions as opposed to equally perceiving the whole image without any attention mechanisms. To generate more appealing corrected results in visual appearance, we introduce a coarse-to-fine inpainting network to fill the hole regions caused by the irreversible mapping function using distortion parameters. Each module of the proposed network is differentiable, and thus the entire framework is completely end-to-end. When compared with the previous supervised methods, our method is more flexible and shows better practical applications for distortion rectification. The experiment results demonstrate that our proposed method outperforms state-of-the-art methods on the correction performance without any labeled distortion parameters.     

利用相移条纹相位解调的广角镜头畸变校正

文中提出了一种基于相移条纹图相位分析的广角镜头畸变校正方法。首先,用大尺寸液晶平板显示器显示四幅相移量为π/2的余弦条纹图作为校正模板。然后,用广角镜头相机拍摄该校正模板,获得四幅畸变条纹图,使用四步相移算法解调径向畸变条纹图的相位分布。由于经广角镜头成像的图像中心区域几乎无畸变,利用图像中心无畸变的相位值进行数值拟合得到径向无畸变条纹图的相位分布,作为求解径向畸变相位的基准,也就是径向畸变相位分布可以根据径向畸变条纹图的相位分布与径向无畸变条纹图相位分布相减得到,再将畸变相位转换成实际的畸变量。提出的方法不需要通过特征点或特征线确定畸变模型,可以直接计算畸变图像中每个像素点的畸变量。实验结果表明,提出的方法简单、有效,具有广泛应用价值。     

基于失真图像特性测量的扫描图像校正技术

提出一种扫描图像校正技术，解决书籍扫描时图像背景灰度不匀、几何畸变和局部模糊的问题。该方法不依赖扫描设备的物理参数，完全根据对失真图像的测量来计算校正因子。选取适当的采样窗1：3，基于直方图分析导出背景灰度因子，通过内插校正几何失真，最后进行空变高通滤波以减轻字迹模糊。通过建立背景灰度因子和缩小系数的关系实现对扫描设备的标定，从而在校正同一设备输出的其它图像时可根据背景灰度的变化而不必再检测页面边缘。与原始扫描图像相比，处理后的图像质量大为改善，且光学字符识别（OCR）处理的识别率达到82．6％。     

Improving geometric accuracy in the presence of susceptibility difference artifacts produced by metallic implants in magnetic resonance imaging

Geometric and intensity distortions due to the presence of metallic implants in magnetic resonance imaging impede the full exploitation of this advanced imaging modality. The aim of this study is to provide a method for (a) quantifying and (b) reducing the implant distortions in patient images. Initially, a set of reference images (without distortion) was obtained by imaging a custom-designed three-dimensional grid phantom. Corresponding test images (containing the distortion) were acquired with the same imaging parameters, after positioning a specific metallic implant in the grid phantom. After determining: 1) the nonrecoverable; 2) the distorted, but recoverable; and 3) the unaffected areas, a point-based thin-plate spline image registration algorithm was employed to align the reference and test images. The calculated transformation functions utilized to align the image pairs described the implant distortions and could therefore be used to correct any other images containing the same distortions. The results demonstrate successful correction of grid phantom images with a metallic implant. Furthermore, the calculated correction was applied to porcine thigh images bearing the same metallic implant, simulating a patient environment. Qualitative and quantitative assessments of the proposed correction method are included.     

皮肤反射式共聚焦显微成像扫描畸变校正

皮肤反射式共聚焦显微镜是一种重要的皮肤影像学诊断工具,其采用共振型振镜扫描成像会带来非线性畸变,为校正这种畸变,提出一种像素值反正弦过采样信号重建的RCM图像畸变校正方法,对间距为20 m的矩形光栅扫描成像实验表明,在校正畸变前光栅图像间距的标准差为7.78 m,图像的畸变率达到38.9%,经过像素值反正弦过采样信号重建后,光栅图像间距的标准差缩小为0.85 m,畸变率缩小到4.2%。结合分辨率板和实际人皮肤成像情况,表明文中提出的畸变校正方法能够较好地校正共振型振镜引起的图像畸变,满足人皮肤实时无创影像学诊断要求。     

高精度图像尺寸检测镜头畸变校正方法与实现

在高精度轴类零件尺寸图像检测中,提出了一种基于标准件法对镜头径向畸变进行快速校正的方法。该方法通过建立世界坐标转换到摄像机坐标、然后再转换到图像坐标的理想数学模型,并引入径向畸变参数,最终确立物体在世界坐标中与图像坐标中的映射关系,从而建立误差补偿曲线的高次拟合函数。利用得到的误差补偿函数的系数矩阵和径向畸变参数,实现镜头畸变的误差校正,有效改善了镜头畸变造成的检测误差。实验表明,该方法快速有效,提高了检测精度、降低了设备成本、检测精度可达2 μm。     

应用频率积分相位解调测量径向畸变

为了测量光学成像系统的径向畸变,采用载频条纹模板,应用瞬时频率积分法提取因径向畸变而产生的径向调制相位;推导了条纹径向调制相位与瞬时频率的关系式,并导出径向调制相位和径向畸变位移关系;采用小波频率估计提取畸变条纹径向瞬时频率,并对其进行积分获得畸变条纹的径向调制相位;应用径向调制相位和立方卷积插值算法对畸变图像进行了校正,得出了详细的理论分析和实验结果。结果表明,上述方法是可行的。     

A rectilinear Gaussian model for estimating straight-line parameters

For characterizing straight lines in defocused images, a rectilinear Gaussian model (RGM) is proposed. Based on this model, a novel method for estimating the parameters of straight lines is presented. This method, called gray-scale least square (GLS) method, directly deals with gray-scale image data without requiring any preprocessing and hence no additional noise is introduced. Furthermore, the method is able to simultaneously estimate four parameters of straight lines by performing the algorithm only once, while two parameters can be typically estimated by traditional method. Besides this, all parameters are given in closed-form solution. In order to illustrate the effectiveness of RGM and the GLS method, the experiments are performed on a set of artificial images and natural images. The experimental results show that the GLS method outperforms the traditional method from the point of view of sensitivity to noise and accuracy of parameter estimation.     

鱼眼镜头图像畸变的校正方法

提出了一种校正鱼眼镜头图像畸变的新方法。通过追迹光学系统的主光线,获得它在投影平面上的径向位置与它在像平面上位置之间的关系曲线;然后用傅立叶级数拟合该关系曲线;并求出该级数的逆函数,结果就可以根据畸变图像复原没有畸变的图像。用该方法数值模拟两个鱼眼镜头系统的图像畸变校正;并用其中一个鱼眼镜头（尼康16 mm/F2.8）拍摄的两张图像进行了畸变校正实验。结果表明,当设置投影平面和物平面重合时,恢复的图像相对于物体的残余径向高度误差非常小（小于0.25%）。实验证明了该方法是可行的。     

基于精确模型和逆投影的超大视场红外图像畸变校正

针对超大视场红外图像畸变大、与人眼视觉差异明显的问题,提出了一种基于精确模型和逆投影的超大视场红外图像畸变校正算法以改善其视觉效果.该算法首先利用精确模型对超大视场红外相机成像中的物、像关系进行描述;然后,针对红外图像像素采样率不高的缺点,利用较为精确的三次卷积插值法对图像进行插值来补全成像信息;最后,根据校正图像上的待赋值像点的坐标,结合校正模型和超大视场红外相机精确模型,计算该像点逆投影到插值图像时的对应坐标,并以最近邻像点像素值作为校正后图像像点的赋值.车载道路场景下的超大视场红外图像畸变校正实验结果显示,所提出的算法图像校正结果边界清晰、无锯齿效应,对场景中的直线平均还原偏差小于0.35 pixels,表明该算法对超大视场红外图像畸变校正具有较好的适用性.     

合作空间目标双基地ISAR图像畸变分析及校正方法

为了解决双基地逆合成孔径雷达（ISAR）二维图像的畸变问题,以平稳运动的合作空间目标 为研究对象 ,从双基地ISAR回波模型出发,研究了图像的畸变机理并提出了基于畸变角估计的图像畸变 校正方法。基于合作空间目标的精轨信息,算法首先估计出成像期间的双基地角,其次利用 图像畸变角与双基地角的关系对畸变角进行估计,然后利用畸变角计算横向畸变单元数,最 后对二维图像进行反向畸变补偿,完成畸变校正。仿真实验验证了算法的有效性。     

Nonmetric calibration of camera lens distortion: differential methods and robust estimation.

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. Our approach is based on the analysis of distorted images of straight lines. We derive new distortion measures that can be optimized using nonlinear search techniques to find the best distortion parameters that straighten these lines. Unlike the other existing approaches, we also provide fast, closed-form solutions to the distortion coefficients. We prove that including both the distortion center and the decentering coefficients in the nonlinear optimization step may lead to instability of the estimation algorithm. Our approach provides a way to get around this, and, at the same time, it reduces the search space of the calibration problem without sacrificing the accuracy and produces more stable and noise-robust results. In addition, while almost all existing nonmetric distortion calibration methods needs user involvement in one form or another, we present a robust approach to distortion calibration based on the least-median-of-squares estimator. Our approach is, thus, able to proceed in a fully automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered projections of three-dimensional linear segments. Experiments to evaluate the performance of this approach on synthetic and real data are reported.     

Restoration of multispectral images by the gradient reconstruction method and estimation of the blur parameters on the basis of the multipurpose matching model

In this study, an original method for restoration of multispectral images by means of gradient reconstruction is proposed. The method uses a simple relationship between the gradient at the neighboring points in the distorted image and the gradient at distant points in the initial image. The result of restoration by the proposed algorithm excels the result obtained by the standard method based on the Wiener filtering. A new method for estimation of the parameters of the distorting motion-blur operator is also proposed. In this case, the blurred image is considered as a superposition of M shifted original images, and the autocorrelation convolution of the distorted image can be represented as a linear combination of M ² mutual convolutions of several identical shifted images. Thus, the autocorrelation function of the distorted image is a straight line passing through the center, and the direction of this line and its length coincides with the parameters of the distorting operator. As compared to the best present-day algorithms, the proposed method exhibits higher accuracy of parameter estimation. In addition, computation of parameters with the use of this method takes much less time than with the use of popular estimation algorithms based on the Radon transform.