Paper
8 November 2012 High performance cluster system design for remote sensing data processing
Yuanli Shi, Wenming Shen, Wencheng Xiong, Zhuo Fu, Rulin Xiao
Author Affiliations +
Proceedings Volume 8539, High-Performance Computing in Remote Sensing II; 85390N (2012) https://doi.org/10.1117/12.975805
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom
Abstract
During recent years, cluster systems have played a more important role in the architecture design of high-performance computing area which is cost-effective and efficient parallel computing system able to satisfy specific computational requirements in the earth and space sciences communities. This paper presents a powerful cluster system built by Satellite Environment Center, Ministry of Environment Protection of China that is designed to process massive remote sensing data of HJ-1 satellites automatically everyday. The architecture of this cluster system including hardware device layer, network layer, OS/FS layer, middleware layer and application layer have been given. To verify the performance of our cluster system, image registration has been chose to experiment with one scene of HJ-1 CCD sensor. The experiments of imagery registration shows that it is an effective system to improve the efficiency of data processing, which could provide a response rapidly in applications that certainly demand, such as wild land fire monitoring and tracking, oil spill monitoring, military target detection, etc. Further work would focus on the comprehensive parallel design and implementations of remote sensing data processing.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuanli Shi, Wenming Shen, Wencheng Xiong, Zhuo Fu, and Rulin Xiao "High performance cluster system design for remote sensing data processing", Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 85390N (8 November 2012); https://doi.org/10.1117/12.975805
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Remote sensing

Computing systems

Data processing

Image processing

Image registration

Parallel computing

Image fusion

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