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。     

基于相位相关的匀速直线运动模糊图像位移参数估计

为估算匀速直线运动模糊图像的运动参数,提出了一种基于相位相关分析的图像配准方法。该方法利用傅里叶变换的平移特性,对产生平移的目标图像进行傅里叶变换并计算归一化互功率谱,其傅里叶逆变换对应二维脉冲函数,通过计算脉冲函数峰值坐标获取位移图像之间的亚像元级位移量。结合相位相关配准原理和线性空间不变退化模型,给出了匀速直线运动点扩散函数及其光学传递函数的数学描述;讨论了匀速直线运动模糊对相位相关配准结果的影响,证明了图像经过匀速直线运动退化后,位移图像之间归一化互功率谱具有不变性。实验结果表明：动态运动模糊图像最大检测误差为0.489 pixel,标准差为0.16 pixel。     

基于聚类的相位相关运动估计方法

针对相机运动引起的图像序列运动的问题,提出了一种基于聚类的相位相关块匹配运动估计算法。利用Harris算子分别在相邻帧图像上检测角点,以参考图像角点为中心选取一个矩形块,将块匹配法与相位相关相结合来计算图像间的运动矢量。最后,对获得的多个块的平移量,进行空间聚类从而选取运动估计比较准确的点。实验结果表明：该算法配准精度能达到亚像素,稳定性较好。     

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。     

基于统计分析方法的同步移相干涉图位置配准

使用同步移相干涉仪重建波前相位时,需要对移相干涉图进行准确的位置配准和目标区域确定以保证重建精度和相位解缠绕算法的成功实施。提出一种基于统计分析方法的圆形域同步移相干涉图位置配准技术,对一组包含不同相位分布的干涉图按照对应像素位置进行方差分布函数计算;利用最大组间方差法完成阈值分割,从而分离出干涉图像的背景与目标区域,通过梯度运算检测出目标区域的轮廓;利用改进Hough变换算法估计出各个轮廓的绝对位置和半径参数。数值仿真结果表明,当轮廓半径大于64pixel时,该方法的配准精度可以达到0.5pixel。通过建立自参考同步移相干涉仪对该方法的可靠性与实用性进行实验验证。     

一种目标级的遥感图像变化检测算法

传统的像素级变化检测方法对图像的配准准确度要求较高,因而在实际运用中受到很多限制.在人造目标检测的基础上,提出了一种目标级的基于局部配准误差补偿的变化检测方法.根据遥感图像中人造目标与自然目标的纹理差异,对图像中的人造目标进行检测和分割,再对分割图像采用提出的算法进行变化检测.实验表明,与传统的像素级变化检测方法相比,本算法具有较高的检测准确度,对配准准确度的要求也有所放宽,并且可以简化变化检测前的辐射校正工作和变化检测后的像素分类的工作.     

两阶段旋转、平移亚像素数字稳像算法

提出一种稳健的两阶段层次匹配稳像算法, 在频域结合相位相关和谱对消技术对抖动图像序列间的平移和旋转矢量获得亚像素估计精度。算法第一阶段首先在对数极坐标表示下, 利用相位相关法得到图像帧间的旋转角度和整数像素平移参数; 算法第二阶段运用谱对消技术确定亚像素平移参数。在建立参数运动模型的基础上,通过自适应均值滤波确定各帧修正矢量。实验结果表明, 该方法具有亚像素级的稳像精度。     

基于印刷缺陷检测的图像配准方法研究

图像配准是机器视觉和图像处理的重要研究内容,针对印刷缺陷检测中图像配准效率低、误差大等问题,提出了区别于普通连续色调图像的新方法。采用数学形态学和Hough变换的方法检测图像配准的旋转角和缩放因子,并基于相位相关原理对傅里叶变换的范围进行改进,求取待检图像和标准图像之间的相对偏移量,最终实现文本印刷图像的高效配准。实验结果表明,平均配准误差控制在1个像素范围以内,而且整个配准过程在1s内完成,对文本图像具有较好地配准效果,能为文本印刷品的质量检测奠定良好的基础。     

多角度偏振成像仪在轨图像配准及性能评估

高精度的图像配准是保证多角度偏振成像仪在轨数据有效性的关键.介绍了多角度偏振成像仪基于光楔的偏振图像配准方法和基于地球参考网格的多角度、多光谱图像配准方法 .系统地分析了影响多角度偏振成像仪多角度、多光谱图像配准性能的误差,并提出通过相对几何定标提高多角度、多光谱图像配准性能.对比误差校正前后多角度偏振成像仪的多角度、多光谱图像配准性能,证明所提方法有效地提高了多角度、多光谱图像配准精度.多角度偏振成像仪在轨多角度、多光谱和偏振图像配准精度分别优于0.26 pixel、0.14 pixel和0.1 pixel.     

基于超分辨率重建的图像增强算法研究

 为了提高图像分辨率,从软件的角度出发,对低分辨率图像序列重建高分辨率图像的原理和算法实现开展了研究,提出从多个低分辨率图像序列中获取更高分辨率图像的方法。通过采用基于光流场的金字塔分层结构实现由粗到精的图像配准,获取了亚像素的运动估计。在采用多帧低分辨率图像进行亚像素级配准后,提出采用动态自适应确定正则化参数的方法,构造了简单的正则化代价函数,建立了低分辨率图像与高分辨率图像之间关系的重建模型,仿真实验结果表明该超分辨率重建算法水平和垂直方向上分辨率各增加一倍,与其他算法相比清晰度更高,计算时间不到传统POCS算法的一半。     

Image improvement based on sub-pixel post-integration for a staring imaging system in geostationary orbit

This paper proposes the post-integration technology based on sub-pixel image registration and image fusion to improve the signal-to-noise ratio （SNR） of remote sensing images without motion degradation caused by satellite vibration. A two-dimensional vibration system is set up to simulate satellite disturbance. Image sequences with different exposure times are captured using a high-speed CMOS camera. The displacement plots are compared with the motion data measured by the grating linear encoder. These plots indicate that the accuracy of the registration algorithm is better than 0.1 pixels. The sub-pixel image fusion shows an improvement in image quality, thus indicating that this technology is powerful for staring imaging systems in geostationary orbit.     

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.     

基于特征匹配的快速鲁棒数字稳像

针对手持移动摄像装置拍摄视频序列相邻帧间存在平移、小角度旋转运动,而且易受噪声、光照变化的影响等问题,提出一种基于优化Oriented FAST and rotated BRIEF(ORB)特征匹配的实时鲁棒电子稳像算法。对相邻帧预处理后用Oriented FAST算子检测特征点,再用Rotated BRIEF描述提取的特征点并采用近邻汉明距离匹配特征点对,然后采用级联滤波去除误匹配点对,最后使用迭代最小二乘法(ILSM)拟合模型参量进行运动补偿实现稳像。图像匹配测试和稳像实验结果表明:基于改进的ORB算法的电子稳像方法补偿每一帧的时间均小于0.1 s,定位精度可达亚像素级,能有效补偿帧间平移旋转运动,而且对噪声和光照变化有较强鲁棒性。经稳像处理后,实拍视频质量明显提高,峰值信噪比（PSNR）平均提高了10 db。     

列图像中遮挡缺损图像补偿算法

针对动态图像的遮挡缺损问题,提出了基于图像块的帧间预测算法,可以检测出序列图像中的遮挡缺损区域;利用帧间灰度相关性修正补偿算法进行遮挡缺损区域补偿,利用修正的像元对缺损区域进行补偿能够克服传统插值补偿算法补偿痕迹明显的缺点.仿真结果表明:该算法补偿处理区域与邻域灰度过渡平滑,消除了补偿痕迹,补偿效果比较理想.     

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.     

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.