图像配准和融合及其在医学影像中的应用

图像配准和融合是图像分析和处理的基本问题，在医学影像、遥感、计算机视觉等领域有着广泛的应用。本文研究它们在多模态医学影像技术中的应用。本文提出并实现了基于Ｆｏｕｒｉｅｒ变换的图像配准和基于子波变换的图像融合方法，在图像融合中，我们采用特征选择的取大原则，这种准则更适合于来自不同图像中的明显特征     

Automatic registration of aerophotos based on SUSAN operator

The technique of image matching is the basis of image fusion,image mosaic and scene 3D reconstruction.In the paper a novel image registration method based on SUSAN operator is proposed.Firstly,Corner points are extracted by using SUSAN(Smallest Univalue Segment Assimilating Nucleus) operator.Then matched corner points are selected through coarse matching and fine matching.Based on such corner pairs,aerophotos are registered automatically.     

干涉雷达在DEM测量中的精度影响及处理方法

干涉合成孔径雷达 (INSAR)为数字高程模型 (DEM)测量提供了一种新的手段。它具有同时获取三维信息、测量范围广、空间和高程分辨率高等优点。文中首先扼要介绍了干涉雷达的原理 ,然后重点讨论几个影响测量精度的因素及其处理方法 ,如相关、运动补偿、配准、相位展开等。     

Automatic registration of optical imagery with 3D LiDAR data using statistical similarity

The development of robust and accurate methods for automatic registration of optical imagery and 3D LiDAR data continues to be a challenge for a variety of applications in photogrammetry, computer vision and remote sensing. This paper proposes a new approach for the registration of optical imagery with LiDAR data based on the theory of Mutual Information (MI), which exploits the statistical dependency between same- and multi-modal datasets to achieve accurate registration. The MI-based similarity measures quantify dependencies between aerial imagery, and both LiDAR intensity data and 3D point cloud data. The needs for specific physical feature correspondences, which are not always attainable in the registration of imagery with 3D point clouds, are avoided. Current methods for registering 2D imagery to 3D point clouds are first reviewed, after which the mutual MI approach is presented. Particular attention is given to adoption of the Normalised Combined Mutual Information (NCMI) approach as a means to produce a similarity measure that exploits the inherently registered LiDAR intensity and point cloud data so as to improve the robustness of registration between optical imagery and LiDAR data. The effectiveness of local versus global similarity measures is also investigated, as are the transformation models involved in the registration process. An experimental program conducted to evaluate MI-based methods for registering aerial imagery to LiDAR data is reported and the results obtained in two areas with differing terrain and land cover, and with aerial imagery of different resolution and LiDAR data with different point density are discussed. These results demonstrate the potential of the MI and especially the CMI methods for registration of imagery and 3D point clouds, and they highlight the feasibility and robustness of the presented MI-based approach to automated registration of multi-sensor, multi-temporal and multi-resolution remote sensing data for a wide range of applications.     

利用形状匹配技术作数字图象对位

本文提出一种利用区域形状匹配技术来实现数字图象的自动对位的方法。利用对噪声和畸变相对稳定的弦分布形状匹配法,建立由待定位图象中分割出来的区域之间的相似关系。用概率松弛标签算法优化和确认匹配,进而得出对位所需的变换参数。分析和实验均表明:这种方法对有未知比例,位移和旋转变化的图象的对位效果良好。     

Using snakes for the registration of topographic road database objects to ALS features

For historical reasons many national mapping agencies store their topographic data in a dual system consisting of a Digital Landscape Model (DLM) and a Digital Terrain Model (DTM). The DLM contains 2D vector data representing objects on the Earth’s surface, such as roads and rivers, whereas the DTM is a 2.5D representation of the related height information, often acquired by Airborne Laser Scanning (ALS). Today, many applications require reliable 3D topographic data. Therefore, it is advantageous to convert the dual system into a 3D DLM. However, as a result of different methods of acquisition, processing, and modelling, the registration of the two data sets often presents difficulties. Thus, a straightforward integration of the DTM and DLM might lead to inaccurate and semantically incorrect 3D objects.In this paper we propose a new method for the fusion of the two data sets that exploits parametric active contours (also called snakes), focusing on road networks. For that purpose, the roads from a DLM initialise the snakes, defining their topology and their internal energy, whereas ALS features exert external forces to the snake via the image energy. After the optimisation process the shape and position of the snakes should coincide with the ALS features. With respect to the robustness of the method several known modifications of snakes are combined in a consistent framework for DLM road network adaptation. One important modification redefines the standard internal energy and thus the geometrical model of the snake in order to prevent changes in shape or position not caused by significant features in the image energy. For this purpose, the initial shape is utilized creating template-like snakes with the ability of local adaptation. This is one crucial point towards the applicability of the entire method considering the strongly varying significance of the ALS features. Other concepts related to snakes are integrated which enable our method to model network and ribbon-like characteristics simultaneously. Additionally, besides ALS road features information about context objects, such as bridges and buildings, is introduced as part of the image energy to support the optimisation process. Meaningful examples are presented that emphasize and evaluate the applicability of the proposed method.     

Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency.     

基于特征提取的光学影像和SAR影像自动配准

针对现有的配准方法用于多光谱影像与SAR遥感影像配准时，存在受SAR图像斑纹噪声影像大、手工选取配准控制点精度低、利用图像景物特征配准时获取区域和边沿困难等问题，以SPOT5影像与RADARSATSAR影像配准进行实验，提出了一种利用改进的SIFT在提取的特征图像上寻找匹配点进行粗配准，然后利用交叉累积剩余熵作为相似性测度结合原始影像信息寻找光学特征图像的角点在SAR影像上的匹配点并进行精配准的方法，配准精度达到了子像素级水平。实验结果表明该方法对多源遥感影像有很强的适应性，配准精度高。     

基于地学信息服务的Internet 3维 GIS：GeoEye 3D

随着Internet、分布式计算以及计算机图形学的飞速发展,开发基于Internet的3维GIS系统已成为可能。这3种技术的有力结合为地学领域开创了一个崭新的时代,促使网络GIS的概念由“地学数据服务”提高到“地学信息处理服务”的新阶段,不仅地学数据,地学信息处理功能也可以分布在基于客户／服务器的架构上,用户可以根据不同的需求“租用”和组合来自于Internet的不同功能。基于这一概念和作者提出的构件注册模型,我们从1998年开始着手研究和开发新一代的Internet 3维GIS：GeoEye 3D。这一系统集成了GIS、3维可视化、分布式计算及网络通信等技术,允许用户通过标准Internet浏览器来应用远程功能对远程和本地数据进行可视化分析。阐述了地学信息处理服务概念和构件注册模型以及GeoEye 3D的系统架构、算法和应用实例。     

Radargrammetric registration of airborne multi-aspect SAR data of urban areas

In this paper, the registration of decimeter-resolution airborne multi-aspect SAR (MASAR) data of inner city areas by application of the radargrammetric range-Doppler equations is investigated. The geometrical model is adapted to linear flight trajectories and zero-Doppler processed SAR data, whereas the observed trajectory parameters are adjusted using a strict Gauss–Helmert model and known ground control points. The significance of the estimated corrections is examined and the most suitable set of free parameters is determined. Finally, the methodology is applied to real test data of an airborne campaign over the city of Munich, Germany, and the feasability of the proposed radargrammetric registration method is shown.