上海交通大学硕士学位论文 摘要 第 I 页 多源动态图像序列配准研究 摘多源动态图像序列配准研究 摘 要要 图像配准最早于二十世纪七十年代美国从事的飞行器辅助导航系统、武器投射系统的制导和寻地等应用研究中提出。随着科学技术的发展, 图像配准（或匹配）技术已成为近代信息处理领域中一项极为重要的技术, 它的应用范围也更加广泛, 其中包括: 计算机视觉和模式识别，服务于目标识别、形状重建、运动监测和特征识别等等；医学图像分析，如肿瘤检测、病变定位，大脑或血管造影、血细胞显微图像分类等；遥感图像分析，农业、地理、海洋、石油、地矿勘探 、污染、城市森林等；军事上，可用于导弹的地形和地图匹配制导，飞航导弹、武器投射系统的末制导和寻踪，光学和雷达的目标跟踪；以及资源分析, 气象预报,景物分析中的变换检测等各个方面。图像配准，即对同一个景物在不同时间、用不同探测器、从不同视角获得的图像，利用图像中公有的景物，通过比较和匹配，找出图像之间的相对位置关系。更准确的说，图像配准的目标就是找到把一幅图像中的点映射到另一幅图像中对应点的最佳变换。 静态图像配准需要解决的问题是两幅图像在空间域上的对应关系，然而在实际应用中,有时需要同时考虑两幅图像在时间域上的对应关系,这反映在对两个图像序列进行配准的问题上。例如,多传感器目标识别中,利用可见光和红外传感器对运动目标进行图像采集而分别得到两个图像序列，在进行融合目标识别之前,首先需要对这两个图像序列进行配准。上海交通大学硕士学位论文 摘要 第 II 页 研究序列图像配准问题主要有两个目的：1、解决单幅图像配准中出现的空间歧义问题，并用于处理许多单幅图像配准不能处理的情况：(1)解决空间歧义。(2)提高配准精度。(3)减少组合复杂度。2、配准融合多个图像序列在时间、空间上的信息，并催生了新的视频应用：(1)时间、空间的超分辨率。 (2)多传感器图像配准。 本文总结前人在动态图像序列配准方面的一些研究成果，包括基于基准帧图像、基于特征、基于区域的等图像序列配准方法，深入研究动态图像序列配准中的时间对应性求解及克服多传感器图像差异显著的问题。针对红外和可见光图像序列的配准问题，提出了能够满足一定实时性要求和精确度的配准方法，主要的研究内容包括以下几方面： 1、研究多传感器图像的配准问题，针对多传感器图像差异较大的特点，总结前人方法，改进了基于高通能量变换的多传感器图像配准方法，较好的克服了多传感器引起的差异问题，同时具备较好的实时性与精确性，并以此作为序列图像配准中对应帧配准的方法。 2、研究基于轮廓匹配的图像配准方法，改进了轮廓匹配方法，实现了改进 8 邻点链码的轮廓匹配方法，提高了轮廓匹配的效率和精确性。 3、研究基于运动目标尺度变化的图像序列配准方法，根据运动目标的尺度变化曲线求取图像序列的时间对应关系，利用基于高通能量变换的图像配准算法实现对应帧图像配准，从而实现图像序列配准。 4、研究基于运动轨迹的图像序列配准算法，将运动轨迹以轮廓的形式表示，利用轮廓匹配算法实现匹配，最终同步解决图像序列的时间与空间对应关系。 关键字：图像配准，图像序列配准，高通能量变换，运动轨迹匹配上海交通大学硕士学位论文 ABSTRACT 第 III 页 INVESTIGATION ON REGISTRATION OF MULTI-SOURCE DYNAMIC VIDEO SEQUENCES ABSTRACT Image registration is first proposed in the research of auxiliary navigation system for aircraft, projection system of weapons in American in 1970s. With the development of science and technology, image registration has become a very important technique in the information technology, and has been widely used, such as computer version and pattern recognition, medical image analysis, remote image analysis, and military purposes. Image registration is to get the correspondence between the images of the same scene taken from different view points, at different time, or with different kinds of cameras. The purpose of image-to-image registration is to get the spatial transformation between the two images. However, the temporal correspondence is also required for some cases in the practical applications. Taking target identification for multi-sensor as an example, the sequences are taken from different sensors, so it is necessary to register them before multi-sensor information fusion. There are two main motivations to use sequence-to-sequence registration: (1) it can resolve spatial ambiguities and handle situations that image-to-image alignment can not: resolving the spatial ambiguities, improving accuracy of registration, reducing combinatorial combinatory; (2) it gives rise to new video applications that are very difficult for image-to-image registration: providing super-resolution both in time and space, resolving the image registration for multi-sensor easier using the temporal behaviors in the sequence. 上海交通大学硕士学位论文 ABSTRACT 第 IV 页 This paper reviews the previous achievements in sequence-to-sequence registration, including feature-based, direct-based, and reference-frame-based sequences registration. And much research has been done on how to resolve the correspondence in time and the difficulties caused by multi-sensor. The paper proposes and realizes the registration methods addressing visible light and infra-red sequences, and the experiments show the validity and the accuracy of them. The main research content of the paper is as follow: 1. Analyzed and summarized the previous methods, and improved the methods based on high-pass energy transformation to address the abrupt changes caused by different sensors, which satisfied the acquirement of accuracy and real-time and was used to register the corresponding frames in time domain. 2. Analyzed the registration methods based on matching contours, and realized the matching method using improved 8-d chain codes. And it provided the theoretical support for matching the trajectories. 3. Researched on the sequence-to-sequence registration based on scale change of target. In the method, we acquired the temporal transformation according to the change curves of targets scale, and used the method based on high-pass energy transformation to register corresponding frames to get the spatial transformation parameters. 4. Researched on the sequence-to-sequence registration based on trajectories. In the method, we represented the trajectory in the form of contour, used the contour-matching method to match the trajectories, and finally acquired the correspondence of the two sequences both in time and space. Key words ： Image Registration, Sequence-to-S