钟何平, 唐劲松, 马梦博, 吴浩然. 共享内存环境下的干涉合成孔径声呐复图像配准及优化方法[J]. 武汉大学学报 ( 信息科学版), 2019, 44(8): 1169-1173. DOI: 10.13203/j.whugis20180051
引用本文: 钟何平, 唐劲松, 马梦博, 吴浩然. 共享内存环境下的干涉合成孔径声呐复图像配准及优化方法[J]. 武汉大学学报 ( 信息科学版), 2019, 44(8): 1169-1173. DOI: 10.13203/j.whugis20180051
ZHONG Heping, TANG Jinsong, MA Mengbo, WU Haoran. Complex Image Registration Algorithm and Its Optimization for Interferometric Synthetic Aperture Sonar in Shared Memory Environment[J]. Geomatics and Information Science of Wuhan University, 2019, 44(8): 1169-1173. DOI: 10.13203/j.whugis20180051
Citation: ZHONG Heping, TANG Jinsong, MA Mengbo, WU Haoran. Complex Image Registration Algorithm and Its Optimization for Interferometric Synthetic Aperture Sonar in Shared Memory Environment[J]. Geomatics and Information Science of Wuhan University, 2019, 44(8): 1169-1173. DOI: 10.13203/j.whugis20180051

共享内存环境下的干涉合成孔径声呐复图像配准及优化方法

Complex Image Registration Algorithm and Its Optimization for Interferometric Synthetic Aperture Sonar in Shared Memory Environment

  • 摘要: 提出了一种共享内存环境下的干涉合成孔径声呐(interferometric synthetic aperture sonar,InSAS)复图像配准优化方法。首先在分析复图像配准算法各处理步骤计算特点和并行性的基础上,针对粗配准和精配准计算中大量的滑动窗口计算操作,根据相邻窗口数据之间的关系进行了计算方法优化设计;然后采用OpenMP指令对粗配准、精配准、复图像插值和干涉相位提取计算步骤进行了并行化设计和计算任务分配,以充分利用多核计算资源加速复图像配准过程;最后通过InSAS复图像的并行配准试验验证了所提方法的正确性和高效性。

     

    Abstract: Complex image registration is one of the most important steps during the process of interferometric signal processing, and its efficiency directly affects the performance of interferometric signal processing system. In order to improve the efficiency of complex image registration algorithm, we propose an optimized complex image registration algorithm for interferometric synthetic aperture sonar (InSAS) in shared memory environment. Firstly, after analyzing the characteristic of calculation and parallelism of each processing step for complex image registration, an optimized computation method for coarse registration and refine registration is proposed for the massive sliding operation based on the coherence of data in adjacent windows. Then, in order to make full use of multi-core computing resource to accelerate the process of complex image registration, OpenMP instructions are used to parallel design and task allocation for coarse and refine registration, complex image interpolation and wrapped phase extraction. Finally, the correctness and efficiency of the proposed method are verified by the parallel complex image registration for InSAS.

     

/

返回文章
返回