Improving motion estimation by accounting for local image distortion

Cardiac elastography is a useful diagnostic technique for detection of heart function abnormalities, based on analysis of echocardiograms. The analysis of the regional heart motion allows assessing the extent of myocardial ischemia and infarction. In this paper, a new two-stage algorithm for cardiac motion estimation is proposed, where the data is taken from a sequence of 2D echocardiograms. The method combines the advantages of block-matching and optical flow techniques. The first stage employs a standard block-matching algorithm (sum of absolute differences) to provide a displacement estimate with accuracy of up to one pixel. At the second stage, this estimate is corrected by estimating the parameters of a local image transform within a test window. The parameters of the image transform are estimated in the least-square sense. In order to account for typical heart motions, like contraction/expansion, translation and rotation, a local affine model is assumed within the test window. The accuracy of the new algorithm is evaluated using a sequence of 500 grayscale B-mode images, which are generated as distorted, but known copies of an original ROI, taken from a real echocardiogram. The accuracy of the motion estimation is expressed in terms of errors: maximum absolute error, root-mean-square error, average error and standard deviation. The errors of the proposed algorithm are compared with these of the known block-matching technique with cross-correlation and interpolation in the sub-pixel space. Statistical analysis of the errors shows that the proposed algorithm provides more accurate estimates of the heart motion than the cross-correlation technique with interpolation in the sub-pixel space.     

The combined effect of nonlinear filtration and window size on the accuracy of tissue displacement estimation using detected echo signals

In cardiac elastography, the regional strain and strain rate imaging is based on displacement estimation of tissue sections within the heart muscle carried out with various block-matching techniques (cross-correlation, sum of absolute differences, sum of squared differences, etc.). The accuracy of these techniques depends on a combination of ultrasonic imaging parameters such as ultrasonic frequency of interrogation, signal-to-noise ratio, size of a kernel used in a block-matching algorithm, type of data and speckle decorrelation. In this paper, we discuss the possibility to enhance the accuracy of the displacement estimation via nonlinear filtering of B-mode images before block-matching operation. The combined effect of a filter algorithm and a kernel size on the accuracy of the displacement estimation is analyzed using a 36-frame sequence of grayscale B-mode images of a human heart acquired by an ultrasound system operating at 1.77 MHz. It is shown that the nonlinear filtering of images enables to obtain the desired accuracy (less than one pixel) of the displacement estimation with smaller kernels than without filtering. These results are obtained for two filters--an adaptive anisotropic diffusion filter and a nonlinear Gaussian filter chain.     

基于相位相关的亚像素配准技术及其在电子稳像中的应用

介绍一种基于相位相关的图像配准方法,并将该方法应用于序列图像的运动检测,通过运动补偿,实现了序列图像的稳定输出。采用相位相关配准方法对序列图像进行亚像素精度配准,运用基于最小二乘的曲面拟合法,估计当前图像相对参考图像的亚像素级的平移量。在补偿图像运动时,为保证亚像素级的补偿精度,采用平滑算法,避免在图像补偿时出现马赛克现象。最后,对样本图像进行了亚像素级位移配准和图像补偿对比实验。实验结果表明,提出的方法可以检测到0．01pixel的运动量,最大配准误差为0．008pixel;采用亚像素级运动量补偿图像,最大误差〈0．5。     

扩展目标夏克-哈特曼波前传感器的频域迭代算法研究

扩展目标夏克-哈特曼波前传感器(SH-WFS)子图像之间偏移量的计算是影响波前传感精度的关键,通常采用相关算法来实现,并通过抛物线插值达到亚像元精度。子图像间的相对偏移量计算也可采用频域相移量估算的方法进行计算,频域算法还可通过迭代进一步提高算法精度。对频域迭代算法进行了理论分析、仿真和实验研究,结果表明,频域迭代算法在信噪比高于4…1时,具有比抛物线插值法更高的计算精度;在信噪比较低时,与抛物线插值法精度相近。     

一种基于自适应补偿的快速帧速率上转换算法

提出一种基于自适应补偿的快速帧速率上转换算法.算法在塔型结构数据上进行运动估计并利用相邻块运动矢量对上层传递矢量进行修正,减少计算量的同时获得了平滑的运动矢量场.在匹配搜索过程中采用动态调整搜索窗策略,避免了过搜索和搜索不足的问题.运动补偿克服了传统的补偿算法仅采用一种插值方法的不足,根据运动矢量的可靠性分别采用了3种不同的插值方法.为了减少块边缘的失真,采用了重叠块运动补偿的插值方法.在遮挡区域,设计了加权多候选运动矢量插值方法,对前后两帧补偿结果分别赋予不同的权值以减少失真.实验结果表明,该算法与传统算法相比不仅可以大幅度降低计算量,且插值图像的质量有所提高.     

基于广义正交迭代算法的立体视觉定位

提出了一种新的基于广义正交迭代算法的立体视觉定位.该算法通过提取CenSurE局部特征和相应的U-SURF描述符,采用SAD方法进行子像素立体匹配,并利用U-SURF描述符匹配进行前后帧图像特征跟踪.在RANSAC框架下对匹配点进行3D-3D运动估计获得了运动参量的初始值.由于3D-3D运动估计使3D点集间欧式距离误差最小,而3D特征点坐标受噪音影响很大,因此运动估计误差也较大.本文把广义正交迭代算法应用到立体视觉定位方法中,得到使立体相机目标空间共线性误差最小的运动估计参量,由于共线性误差比3D-3D运动估计算法中的共点误差受噪音影响更小,从而大大较少了运动估计误差.仿真实验和户外真实实验表明：本文算法获得了较高的计算准确度、鲁棒性和实时性,优于传统方法.     

基于Powell算法的亚像元配准方法

基于Powell优化算法和图像的金字塔分解,提出了一个新的亚像元运动参数估计方法.用参考图像和待配准图像构造的非线性最小二乘公式作为Powell算法的目标函数,并且以运动参数作为变量.由细到粗的多分辨率分解为准确的亚像元参数估计提供了基础.数值实验结果表明,该算法可以用于准确的稳健的亚像元参数估计,其不足之处在于运行时间比较长.     

Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors

The performance of digital image correlation (DIC) is influenced by the quality of speckle patterns significantly. Thus, it is crucial to present a valid and practical method to assess the quality of speckle patterns. However, existing assessment methods either lack a solid theoretical foundation or fail to consider the errors due to interpolation. In this work, it is proposed to assess the quality of speckle patterns by estimating the root mean square error (RMSE) of DIC, which is the square root of the sum of square of systematic error and random error. Two performance evaluation parameters, respectively the maximum and the quadratic mean of RMSE, are proposed to characterize the total error. An efficient algorithm is developed to estimate these parameters, and the correctness of this algorithm is verified by numerical experiments for both 1 dimensional signal and actual speckle images. The influences of correlation criterion, shape function order, and sub-pixel registration algorithm are briefly discussed. Compared to existing methods, method presented by this paper is more valid due to the consideration of both measurement accuracy and precision.     

基于频谱Sevcik维数的目标运动速度估计*

在声目标无源估计应用中,目标与接收器存在相对运动时,接收的目标辐射的噪声信号存在多普勒频移。多普勒频移中包含目标的运动参数信息。针对线谱信号多普勒频移目标运动参数获取问题,提出一种基于频谱Sevcik维数的目标运动速度获取方法。首先利用Doppler-warping变换对接收信号进行重采样,然后对重采样后的频谱信号求Sevcik维数,最后通过寻找Sevcik最小值来实现速度估计。仿真证实了所提方法的有效性,在相同仿真条件下,所提方法相较于频谱求熵算法,速度搜索结果不仅具有更窄的主瓣宽度,而且可提高抗噪性5dB左右。两组实验数据的速度估计误差小于5%,证明了本文算法的有效性。     

低曝光条件下遥感相机微振动量检测

针对搭载平台颤振对遥感相机成像的影响,利用辅助高速面阵CCD相机拍摄高帧频图像序列,通过像元合并来补偿曝光时间不足,增加图像的亮度、对比度和信噪比,同时结合一种区域选择算法来选择用于计算的图像区域,最后使用灰度投影算法对振动位移量进行估计.实验数据表明,提出的改进算法误差为一个像元,在准确性和稳定性方面均明显优于原始算法.     

The application of improved block-matching method and block search method for the image motion estimation

Image block matching is one of the motion estimation methods for video inter-frame coding and digital image stabilization. The methods used for matching and searching will greatly affect the accuracy and speed of block matching. The block matching method based on the oblique vectors is suggested in this paper where matching parameters contain both horizontal and vertical vectors in the image blocks at the same time. Improved matching information can be obtained after making correlative calculations in the oblique direction. A novel search method of matching block based on the idea of simulated annealing is presented in this paper to improve the searching speed, accuracy and robustness in the fast operation of the block-matching motion estimation. The simulated annealing algorithm can easily escape from the trap of local minima effectively. With the two methods the block matching can be used for motion estimation at the real-time image processing system and high estimation accuracy can be achieved. An image stabilization system based on DSP (Digital Signal Processing) system is developed to verify this algorithm. Results show that both the matching accuracy and the search speed are improved with the methods presented.     

激光散斑的亚像素位移法计算及比较

根据激光散斑相关测量中采用的插值法、梯度算法和牛顿一拉夫森迭代法3种亚像素位移算法的特点,逐一在亚像素尺度计算出磁流体干燥过程中的同一激光散斑图的偏均值和标准差变化曲线。基于得到的偏差均值和标准差讨论了3种算法处理激光散斑图的特点,比较了3种算法处理散斑图的计算精度、稳定性和计算用时。结果显示,在小变形的亚像素位移测量时,梯度算法的精度较高,且较为稳定,计算效率也较牛顿一拉夫森算法快约9倍。因此,在进行小变形亚像素位移测量时,采用梯度算法计算激光散斑是有效的。     

基于SIFT匹配的全局运动估计方法

提出了一种基于SIFT(Scale invariant feature transform)匹配的全局运动估计算法.在SIFT初匹配的基础上,对每一个原始匹配特征点,利用所在尺度的邻域灰度信息,对其加权平均后再进行匹配,进而去除误配点.精炼后的匹配点集合作为求解全局运动参数模型的对应数据,采用最小二乘法计算模型参数.在...     

一种空域和频域相结合的运动图像亚像素配准技术

针对视频图像运动检测问题,提出了一种结合空域灰度投影和频域相位相关的亚像素图像配准方法。首先,采用灰度投影算法在空域对运动图像进行粗配准,即在图像行和列方向上计算图像灰度投影特征数据,根据灰度相关函数最小化准则,估计像素级运动量;然后,在经过粗配准的两幅图像中心选取尺寸相同的区域,进行快速傅里叶变换,在频域采用扩展的相位相关算法对图像进行精确配准。该方法利用图像的功率谱信息,减少对图像内容的依赖,运用基于最小二乘的曲面拟合法,实现亚像素图像配准参数估计,具有从粗到精的特点,有效提高了图像检测精度。文中最后对样本图像进行了图像配准对比实验,结果表明,该方法可以检测0.01 pixel的运动量,最大配准误差为0.004 8 pixel。     

一种基于边缘特征的亚像素投影配准算法

为了提高红外图像配准准确度,充分利用图像的边缘信息,结合线性插值,对原有的投影算法引入新的图像相似性评价函数——均方误差函数(Mean Sequare Erron,MSE),提出了基于边缘特征的亚像素投影配准算法.提取图像边缘特征明显的部分做配准能提高匹配概率,引入积分投影能有效降低算法的计算复杂度.算法中还运用了线性插值,使配准准确度达到亚像素级水平.     

MEMS动态测试系统及其数据处理

介绍了基于频闪显微干涉技术的MEMS动态测试系统的测量原理,设计了数据分析处理算法。采用基于立方插值的亚像素模板匹配技术实现了1/50像素的面内位移测量精度。利用分割线去包裹算法实现了从干涉图到三维形貌图的重构。     

联合变换相关器像移测量试验系统设计

为了测量卫星姿态不稳定或振动等原因引起的空间相机亚像元像移,设计了基于联合变换相关器的像移测量试验系统。阐述了该方法的数学原理,面阵CCD的安装位置以及输入图像序列的获取方法。根据相关参数确定了试验系统的傅里叶透镜结构和参数,最终设计了试验系统。应用线性插值和像元合并方法获得具有亚像元像移的图像果表明,像移测量的精度不随景物的内容而变化,测量得到的像移误差均方根值<0.2pixel。     

一种基于相位相关的亚像素红外图像配准算法

图像匹配技术广泛应用于各种图像处理任务,如图像拼接、机器视觉等。通常匹配算法的精确度只能达到像素级别,但在很多图像处理任务如超分辨率重建中需要亚像素精度的图像配准。提出了一种基于相位相关的亚像素图像配准算法。根据两幅离散数字图像的相位相关矩阵中的最大值以及其附近若干点可以拟合估计出实际的峰值位置,进而实现两幅图像的亚像素运动估计。提出的算法针对热像仪采集的红外图像进行匹配实验,实验结果表明该算法精度相比通常的亚像素匹配算法较高,且具有更好的实用性。     

Density and temperature reconstruction of a flame-induced distorted flow field based on background-oriented schlieren(BOS) technique

An experimental system based on the background-oriented schlieren(BOS) technique is built to reconstruct the density and temperature distribution of a flame-induced distorted flow field which has a density gradient. The cross-correlation algorithm with sub-pixel accuracy is introduced and used to calculate the background-element displacement of a disturbed image and a fourth-order difference scheme is also developed to solve the Poisson equation. An experiment for a disturbed flow field caused by a burning candle is performed to validate the built BOS system and the results indicate that density and temperature distribution of the disturbed flow field can be reconstructed accurately. A notable conclusion is that in order to make the reconstructed results have a satisfactory accuracy, the inquiry step length should be less than the size of the interrogation window.     

基于大数据分析的移动对象轨迹预测方法

对移动对象的轨迹预测将在移动目标跟踪识别中具有较好的应用价值。移动对象轨迹预测的基础是移动目标运动参量的采集和估计,移动目标的运动参量信息特征规模较大,传统的单分量时间序列分析方法难以实现准确的参量估计和轨迹预测。提出一种基于大数据多传感信息融合跟踪的移动对象轨迹预测算法。首先进行移动目标对象进行轨迹跟踪的控制对象描述和约束参量分析,对轨迹预测的大规模运动参量信息进行信息融合和自正整定性控制,通过大数据分析方法实现对移动对象运动参量的准确估计和检测,由此指导移动对象轨迹的准确预测,提高预测精度。仿真结果表明,采用该算法进行移动对象的运动参量估计和轨迹预测的精度较高,自适应性能较强,稳健性较好,相关的指标性能优于传统方法。