项目名称: 基于结构不变量的航空遥感图像快速匹配模型和匹配策略研究
项目编号: No.61201454
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 电子学与信息系统
项目作者: 刘朝霞
作者单位: 大连外国语学院
项目金额: 22万元
中文摘要: 作为图像的抽象信息,图像的空间结构是图像配准中可靠的高级特征。基于空间结构的图像配准算法目前已成为图像配准领域中一个新的研究方向。针对遥感图像配准中由于重叠区域低、特征单一、大尺度仿射变换及动态变化导致的匹配不一致性问题,本项目将对图像的空间结构信息进行深入研究和探索,构造空间不变量。同时考虑图像的局部结构信息、全局结构信息、匹配约束、决策限定等问题,建立基于空间结构特征的遥感图像快速匹配模型。利用图匹配的思想对其进行简化,并转化为满足压缩映像定理的方程求解。然后提出基于双向空间约束TSOC和误差限定ER的格外点过滤策略,该策略将大大提高规模大且干扰点多的点集的配准速度。继而采用机器学习的方法实现参数的选取,提高配准算法的鲁棒性。最后对算法的效率进行分析和验证。 本课题将为航空遥感领域图像配准拓展新的研究思路,提供健壮的图像配准方法,填补海上航空遥感图像配准的空白。
中文关键词: 航空遥感图像;特征描述符;特征匹配;结构特征;目标识别
英文摘要: Compared with local feature descriptor, the spatial structure is a higher level and reliable constraint to match feature point sets in image registration. Therefore, image registration algorithm based on spatial structure becomes one of hot topics in image registration.To solve the ambiguity caused by dynamical objects, illumination change, large geometric transformation, similar patterns and low overlapping area between images, spatial structure information will be analyzed in this research. Based on local and global structure information, matching constraints and decision criterias will be defined and a new feature matching model for aerial images regestration will be proposed. A graph matching method will be used to simplify the model and will be solved by the solution of the equation satisfying the contraction mapping principle.Then, A filtering strategy based on TSOC (Two-way Spatial Order Constraint) and ER (Error Restriction) is designed to speed the searching process. This strategy will greatly improve the registration speed for the large point sets with more outliers.After that, the parameter of the algorithm can be optimized by machine learning to improve the robustness of the registration algorithm. At last, the efficiency of the algorithm are analyzed and evaluated. The research will enrich the idea
英文关键词: Aerial Image;Feature Descriptor;Feature Matching;Structure Feature;object detection