【作者】 卢丽君；

【导师】 廖明生；

【作者基本信息】 武汉大学 ， 摄影测量与遥感， 2005， 硕士

【摘要】 利用合成孔径雷达干涉测量(InSAR)技术获取地表的高程信息和形变信息已经在地形测绘、地震火山监测、地表沉降和冰川移动等多个领域得到了越来越广泛的关注。在InSAR影像处理中,配准同一地区的两幅或多幅影像是指准确地提取不同影像在同一点的相位信息,是整个InSAR影像处理流程中一个重要的步骤。同时这一步骤处理结果对流程中的后续步骤起着关键的制约作用,通常要达到子像元的配准精度。 本文系统地分析了现有的InSAR影像配准算法的特点,针对InSAR影像自身的特点,研究了二种多级匹配算法。一种是基于相关系数法和最大干涉频谱法的多级配准算法,另一种是基于相关系数法和最小二乘法的多级配准算法。在粗配准过程中,两种算法都利用相关系数法得到像素级的配准结果,为精配准提供了初始点。在精配准过程中,两种算法分别应用最大干涉频谱法和最小二乘法得到了子像素的配准结果,满足了精度要求。 为了证明两种算法的有效性,分别选取不同地形特点的实验区进行实验,达到了满意的配准效果。同时论文进一步从有效性、可靠性、精度、配准质量、计算时间多个角度比较了两种算法的整体性能,得出了一些有益的结论。 针对InSAR影像的大数据量处理,并行处理是一个很好的选择,它充分地利用了现有的计算资源,同时具有很好的扩展性。考虑到处理大数据量的计算效率、计算精度和计算成本等因素,本文构建了一个可靠的、稳健的分布式并行计算环境,即在PC机群上用统一的中间件(MPI)实现了并行系统的构架。 本文以基于相关系数法和最大干涉频谱法的多级配准算法并行化处理为例,在并行系统构架下实现了并行配准算法,得到了较高的计算效率。并通过对并行算法性能的检测,系统分析总结了影响并行处理几个重要因素。更多还原

【Abstract】 Interferometric Synthetic Aperture Radar (InSAR), as a rising technology in deriving elevation data and slight deformation of earth surface, has drawn extensive attention in various fields such as topographic mapping, monitoring of earthquakes, volcanoes, land subsidence and glacier dynamics and other thematic mapping applications. Registration of two or more images of the same scene is an important procedure in InSAR image processing that seeks to extract differential phase information not obtainable from each one of these images. Meanwhile, the accuracy of this step is crucial to the reliability of subsequent image processing and final results of the data processing chain, meeting subpixel precision request. After analyzing systematically some conventional InSAR registration methods, his paper presents two multi-step image matching algorithms based on the characteristics of InSAR image. One approach is integrating correlation-registration and Max-spectrum image registration, the other is integrating correlation-registration and least square-registration. In coarse mage registration, two approaches all utilize correlation-registration to obtain pixel-accuracy registration results, offering crude control points pairs for the next matching. In precise image registration, two approaches respectively apply Max-spectrum and least square-registration method to register images, the matching accuracy reaches to about subpixel.For purpose of proving validity of the registration method, Experimentations are implemented on several different test sites and meet the request of registration. The paper compares further the two algorithms from some aspects of validity, reliability, registration quality and computing time and obtain some beneficial results.So far, parallel processing is a perfect alternative for InSAR image processing for its capability of fully utilizing available computing resources and high scalability. Considering the requirements of processing highly massive image data in efficiency, accuracy and computation cost, the robust and reliable computation architecture is constrcucted on cluster of PCs by MPI middleware .As a trial on parallel processing, the paper implements a parallized registration algorithm on cluster of PCs and parallel computing environment , showing advantages compared with serial coregistration algorithm. By a few performance criterion tests, several important factors that have greatly effects on parallel system have been analyzed in detail.更多还原