3-D imaging and modeling – Part I: acquisition and registration

The key modules in a typical reverse engineering system consist of the acquisition, registration, and the integration of range images of three-dimensional objects with complex geometry. We first present a self-made optical digitizer that is employed for quickly acquiring range data from multiple views, then introduce a visualized registration procedure that can provide a reliable estimate for the fine registration of multiple range images in a unified coordinate system. Experiment results are given to show the effectiveness of this approach in 3-D imaging and multiple range image registration for the applications of reverse engineering.     

基于分时积分亚像元融合的地球静止轨道平台消颤振技术

相较于低轨卫星线阵扫描成像模式,地球静止轨道面阵成像的曝光时间相对更长,更容易受到平台颤振的影响而造成图像模糊.为了消除由平台颤振引起的像质退化,本文提出了基于分时积分亚像元融合的方法.由于地球静止轨道的凝视成像特性,相机观察区域在长时间内保持不变,因此分时短曝光可以获得多帧目标内容相同,但模糊尺度更低的短曝光图像.然后对多帧短曝光图像采用基于能量区域质心法的相位相关算法进行亚像元图像配准,计算相对偏移量并进行补偿,位移探测准确度可达0.1像元以内,满足卫星平台应用需求.再按亚像元偏移量对多帧图像进行融合,融合的过程可以提升由于曝光时间缩短而降低的单帧图像信噪比,最终可以获得图像清晰度更高、信噪比与原长曝光图像相当、信息辨识度更好的遥感图像.     

基于分时积分亚像元融合的地球静止轨道平台消颤振技术

相较于低轨卫星线阵扫描成像模式,地球静止轨道面阵成像的曝光时间相对更长,更容易受到平台颤振的影响而造成图像模糊.为了消除由平台颤振引起的像质退化,本文提出了基于分时积分亚像元融合的方法.由于地球静止轨道的凝视成像特性,相机观察区域在长时间内保持不变,因此分时短曝光可以获得多帧目标内容相同,但模糊尺度更低的短曝光图像.然后对多帧短曝光图像采用基于能量区域质心法的相位相关算法进行亚像元图像配准,计算相对偏移量并进行补偿,位移探测准确度可达0.1像元以内,满足卫星平台应用需求.再按亚像元偏移量对多帧图像进行融合,融合的过程可以提升由于曝光时间缩短而降低的单帧图像信噪比,最终可以获得图像清晰度更高、信噪比与原长曝光图像相当、信息辨识度更好的遥感图像.     

非接触三维测量全场结构关系模型分析及系统开发

研究开发了一种基于光栅投影和主动式三角法的高精度三维测量系统。分析了系统的全场结构关系模型及镜头失真对系统的影响,给出了空间三维坐标的详细算法。试验结果表明,系统的测量误差小于0.04mm,测量精度约为0.03mm。多视角测量的拼合结果表明,系统具有良好的360°测量精度,测量精细表面纹理效果好。该系统在反求工程及质量控制等领域具有良好的工业应用前景。     

基于尾流激光雷达的能量对消式大动态接收技术

水下尾流激光雷达在近场就已开始与水体发生了激光的多次散射, 很容易导致接收系统因动态范围不够而饱和, 其反向恢复时间一般长达10² ns级, 影响远场信号接收.本文针对此问题分析了激光水体后向光散射强度衰减规律, 自主研发了一种能量对消式水下激光雷达前端接收系统. 该系统通过在近场强信号尖峰上叠加一个高速反向瞬态对消电流抑制接收系统饱和, 之后将两信号融合, 还原真实回波信号波形.分析了技术难点并给出了解决方案, 讨论了瞬态对消电流的生成时刻对强度的影响规律.经实测与分析, 该系统对消电流脉宽为5 ns, 幅度控制步进为122 nA, 幅度调节范围为135---360 μA, 成功实现了对近场强散射的抑制. 该系统完全可以满足尾流激光雷达大动态探测的需要.     

立体图象的区域特征提取和视差分析

本文提出了一种自动分类立体图象的算法，首先，提取左，右两幅图象的区域特征，然后定义矩阵Ｒ描述左，右图象的关系，最后匹配其区域特征，同时还对的图象的视差进行了讨论。     

An integration method for scanned multi-view range images (MRIs) based on local weighted least squares (LWLS) surface fitting

We present a novel integration method that can fuse registered partially overlapping multi-view range images (MRIs) into a single-layer, smooth and detailed point set surface. A maximum likelihood criterion is developed to detect overlapping points in MRIs. Subsequently, the detected overlapping points are shifted onto a series of piecewise smooth local weighted least squares (LWLS) surfaces to remove bad influence of scanning noises, outliers and large gaps/registration errors. The LWLS surface is fitted in background neighborhood which contains sufficient information to reconstruct local surface accurately. And the shifting operation is done in a concentric tiny neighborhood which contains corresponding overlapping points. Finally, a simple procedure is designed to identify and merge those corresponding overlapping points. The novel method has the advantages of robust to large gaps/registration errors, possessing least squares means and uniform density distribution. Furthermore, the novel method is efficient since only overlapping points are processed and the non-overlapping points are remained as they are. Several state of the art integration methods were employed for comparison study and the experimental results demonstrate the superiority of the novel method.     

基于分段色域颜色模型的高动态范围图像获取与合成

针对普通彩色相机采用多次曝光获取高动态范围图像的技术,提出了一种基于相机分段色域颜色模型的高动态范围图像获取及颜色合成的理论模型和实现方法.介绍了相机分段色域颜色模型的基本结构和建立方法.用NikonD70s彩色相机和修正的sRGB标准颜色转换模型对所提出的理论和方法进行了实验验证.结果表明,所提出的方法可以在普通彩色...     

多传感器图像自动配准技术研究

多传感器图像自动配准技术是军事领域里多传感器图像融合的必要前提。根据配准的步骤综述了现有的多传感器图像自动配准技术,以可见光和红外图像配准为例,提出采用小波变换、图像处理技术和人工智能技术相结合的方法来解决这一难题。     

远距离多源图像融合系统实时配准设计

为了实现全天候多波段远距离实时图像监控,设计了具有微光、红外和可见光融合的光学前端,对多源图像进行实时配准研究。在平行光轴的基础上,通过计算不同视场图像的成像视差,计算仿射变换需要的参数,采用双线性内插算法弥补红外在成像方面与可见光图像的差别,将红外图像的变换制作成查找表存储在图像处理器DM642中,系统通过硬件查找表可以快速实现不同图像的配准变换,实现同步视频的实时配准与融合。实验表明:该设计能够准确地实现多源图像的实时配准,系统经过图像配准、图像融合和伪彩变换处理后的时间约为24.3 ms,系统探测距离大于3 km。     

中药口服液中可见异物检测系统研究

针对目前生产线上中药口服液中可见异物检测系统存在的速度慢、精度低等问题,设计了一种可同时检测多个药瓶的基于机器视觉的异物快速检测系统。介绍了成像系统和机械系统。提出了一种基于边缘轮廓的图像配准算法,有效地消除了药瓶晃动的影响。提出了一种逐点阈值分割图像的二值化方法,能得到质量较好的二值化图像。实验结果表明,该系统能快速、有效地检测出可见异物,能较好地满足在线检测需求。     

Strategy for automatic and complete three-dimensional optical digitization

This Letter proposes a new strategy of a three-dimensional (3D) scanning pipeline to achieve complete 3D digitization of complex objects in a real scene. This strategy consists of a one-dimensional array of optical 3D sensors combined with an automatically controlled turntable. An efficient calibration method for the sensor array is presented to guarantee the accuracy of the 3D measurement. Furthermore, an automatic registration technique is also proposed for aligning multiple range images taken from sensor array. Experiment results are also presented to demonstrate the proposed approach.     

基于折反射原理的层去反求技术研究

为了克服传统层去反求测量中图像衬比度较低的缺陷,提出一种新的基于棱镜反射原理的层去反求图像摄取方法。该方法利用棱镜的全发射和折射作用提高图像衬比度,根据物体反射率的高低可分别采用垂直照明和倾斜照明,分别可获得高衬比度的亮目标暗背景和暗目标亮背景图像,为了校正由于折反射引入的几何变形,推出了相应的数学变换模型。该研究已成功投入实际产品校正的应用中,研究表明这种新的层去法比起传统的层去法不仅在于图像衬比度高,而且物体截面图像的轮廓更清晰可靠、无需填充反差材料,有望在零件及模型的反求测量中发挥较大的作用。     

工业CT图像轮廓提取与优化系统设计

为了有效地提高面向逆向工程的工业CT图像轮廓处理的精准性和计算效率,开发了工业CT图像轮廓提取与优化系统。该系统主要包括图像处理模块、轮廓识别与提取模块、轮廓拟合与优化模块、图像处理经典算法库和数据接口等功能模块,实现了从工业CT图像到轮廓数据的三维点云与轮廓线的标准格式输出,并与逆向工程软件对接。同时,在轮廓拟合与优化模块中,提出了基于全局约束模型的轮廓拟合策略,并采用有向图分解和数值代数相结合的计算方法,提高了轮廓拟合的计算精度和效率。最后通过实例验证了系统的有效性和正确性。     

连续激光干扰效果评估方法北大核心CSCD

采用改进后的图像相关度计算方法,在精确配准干扰前后图像的基础上,以像素为单位计算图像相关度,根据人眼识别效果在评估前确定干扰阈值,计算图像有效干扰像元统计值,定量描述激光干扰效果;开展多波段激光干扰成像系统试验,采集不同干扰功率下的激光干扰图像,评估干扰效果。结果表明,该方法能精确识别图像局部变化,客观反映图像质量变化,对各波段不同功率下的激光干扰成像图像给出科学评估结果,对单对图像的处理速度优于s级,具有一定的工程应用价值。     

A method on calculating high-dimensional mutual information and its application to registration of multiple ultrasound images

Using mutual information as a criterion for medical image registration, which requires no prior segmentation or preprocessing, has been both theoretically and practically proved to be an effective method in these years. However, this technique is confined in registering two images and hard to apply to multiple ones. The reason is that unlike mutual information between two variables, high-dimensional mutual information is ill defined. In textbooks and theoretical essays, three-dimensional mutual information is proposed based on Venn diagram. Unfortunately, mutual information defined in this way is not necessarily nonnegative. In order to overcome the problem, in this paper, we introduce the mutual information matrix. By calculating its eigenvalues, high-dimensional mutual information is defined. This definition is nonnegative, bounded, and could be extended to higher dimensions, thus enables us to register more than three images. In the end, this definition is tested and proved to be effective on registration of multiple US images through simulation.     

Registration and integration algorithm in structured light three-dimensional scanning based on scale-invariant feature matching of multi-source images

Based on the homography between a multi-source image and three-dimensional (3D) measurement points, this letter proposes a novel 3D registration and integration method based on scale-invariant feature matching. The matching relationships of two-dimensional (2D) texture gray images and two-and-a-half- dimensional (2.5D) range images are constructed using the scale-invariant feature transform algorithms. Then, at least three non-collinear 3D measurement points corresponding to image feature points are used to achieve a registration relationship accurately. According to the index of overlapping images and the local 3D border search method, multi-view registration data are rapidly and accurately integrated. Experimental results on real models demonstrate that the algorithm is robust and effective.     

Image registration framework for large-scale longitudinal MRI data sets: strategy and validation

Advanced magnetic resonance imaging (MRI) studies often require the transformation of large numbers of images into a common space. Calculating transformations that relate each image to every other and applying them to the images on demand are theoretically possible; however, these can be computationally prohibitive. Therefore, relating each image to only one other image, then linking those transforms together to relate any two images in the database, may be an efficient alternative. Evaluated were the feasibility and validity of image registration to bring intraindividual MR images into mutual correspondence for longitudinal analysis through the concatenation of precomputed transforms. A longitudinal data set of 10 multiple sclerosis patients with nine serial dual-echo spin-echo, 1.5-T MRI scans was used. Intrasubject registrations were performed stepwise between consecutive images and direct from each time point to the baseline. Consecutive transforms were concatenated and evaluated against direct registrations by comparing the resulting transformed images (using Pearson correlation coefficient). Confounding variables such as time between scans, brain atrophy, and change in lesion load were evaluated. We found the images resampled with the direct and the concatenated transforms to be highly correlated, and there was no significant difference between methods. Differences in brain parenchymal fraction (a measure of brain atrophy) showed significant inverse correlation with the correspondence of the resampled images. Results indicate that concatenating multiple transforms that link two images together produces near-identical results to that of direct registration; thus, this method is both useful and valid.     

一种从粗到精的红外和可见光卫星图像配准方法

气象卫星所携带的多种传感器可以获得可见光、红外、多光谱等多模态的卫星图像,目前处理这些多模态图像的一个重要手段是数据融合分析方法,而获取不同模态图像空间对应关系的图像配准是数据融合分析的前提和基础。针对多模态气象卫星图像的配准问题,重点研究红外图像和可见光图像的配准问题,并根据红外图像和可见光图像的特点,提出了一种由粗到精的两阶段配准方法。在粗配准阶段,将Fourier-Mellin变换应用于红外和可见光图像的边缘图像上,并通过变换图像在频域的关系实现了图像配准仿射变换参数的快速计算;在精配准阶段,基于图像的Harris算子检测红外图像和可见光图像的特征点,并通过特征点局部区域的互相关函数实现特征点的匹配,最终通过匹配特征点求得精确配准的变换参数。文章提出的由粗到精的图像配准方法,有效结合了Fourier-Mellin变换对边缘图像配准的高效性和Harris算子图像配准的准确性,是红外和可见光图像配准的一种新方法。利用FY-2D气象卫星获取的红外和可见光图像进行了配准实验,实验结果表明所提出的方法具有良好的鲁棒性和较高的配准精度。     

Two-step image registration by artificial immune system and chamfer matching

Image registration is the precondition and foundation in the fusion of multi-source image data. A two-step approach based on artificial immune system and chamfer matching to register images from different types of sensors is presented. In the first step, it extracts the large edges and takes chamfer distance between the input image and the reference image as similarity measure and uses artificial immune network algorithm to speed up the searching of the initial transformation parameters. In the second step, an area-based method is utilized to refine the initial transformation and enhance the registration accuracy. Experimental results show that the proposed approach is a promising method for registration of multi-sensor images.