摘要
本文针对遥感图像IHS、HPF、DWT等典型的像素级融合算法,提出并实现了相应的基于数据并行的并行融合算法P-IHS、P-HPF、P-DWT,并在算法时空复杂度分析的基础上进行了通信、I/O优化。针对IKONOS卫星遥感图像在机群系统上的测试结果表明,我们提出的并行算法可获得良好的并行加速比,并行效率较高。这三类算法适合于对实时性要求比较高的遥感应用领域。
In this paper,corresponding to the image fusion algorithms of IHS,HPF,DWT and other typical remote sensing image fusion algorithms,the data parallel algorithms such as P-IHS,P-HPF,P-DWT are proposed. Based on the algorithm complexity analysis of space-time,the communication and I/O optimization are carried out. The IKONOS satellite images tested on a cluster system show that our proposed parallel algorithm can obtain good parallel speedup and high parallel efficiency. These three algoriths are suitable for real-time remote sensing applications.
出处
《计算机工程与科学》
CSCD
北大核心
2010年第9期34-38,46,共6页
Computer Engineering & Science
基金
国家863计划资助项目(2007AA12Z147)
