Srusti Management Review

A Journal of Management & IT

ISSN NO: 0974-4274(PRINT), ISSN NO: 2582-1148(ONLINE)Listed in Ulrich's Periodicals Directory, INDEXED IN J-GATE E-JOURNAL GATEWAY, EBSCOHOST, PROQUEST, U.S.A. & GOOGLE SCHOLAR A Peer Reviewed and Refereed Journal

Parallel Image Processing Based on Superscalar Pipeline

Year 2012
Volume/Issue/Review Month Vol. - V | Spl. Issue II | July
Title Parallel Image Processing Based on Superscalar Pipeline
Authors Biswa Ranjan Acharya
Broad area Parallel Image Processing Based on Superscalar Pipeline
Abstract
This paper presents a parallel image processing model based on pipeline,
concerning the current efficiency of remote sensing image processing, which
cannot meet the need of processing increased number of remote sensing
data. In the multi-core CPU era, the pipeline technology can process the
complex and time-consuming steps of the remote sensing image processing
in superscalar parallel. This model can improve the processing efficiency
significantly. The principles of the pipeline and the parallel computing are
illustrated in detail in this paper. The obtained experimental results show that
the parallel processing model based on pipeline is efficient in the processing
of remote sensing image with large amount of data.
Description In recent years, remote sensing and earth observation technology make new progress continuously. We receive a large number of new geospatial data from many different sensors every day. If we can’t process these data on time, they will lose their value.
File
Referenceses
  • 1. Zhifeng Xiao, Binglong Zhang, State Key
  • Laboratory of Information Engineering in
  • Surveying
  • 2. Xingshu Hu, Jianya Gong, and Jianping Pan,
  • “Current situation of remote sensing technology
  • in the contemporary era and its developing
  • tendency,” Engineering Journal of Wuhan
  • university, vol. 36(3A), pp. 195-198, 2003.
  • 3. National Program for Medium-to-Long-Term
  • Scientific and Technological Development (2006-
  • 2020).
  • 4. Guorui Huang, Pin Zhang, and Guangbo Wei, “Key
  • techniques of multi—core processor and its
  • development trends,” computer engineering and
  • design, vol. 30(10), pp. 2414-2418, 2009.
  • 5. Mattson T G, Sanders B A, and Massing ill B L, “
  • Patterns for Parallel Programming,” New Jersey:
  • Prentice Hall, 2005.
  • 6. Zhenhua Yang, Ming Chen, and Jianxun Zhao, “The
  • Pipeline Technology in Computer,” Science and
  • Technology Information, pp. 79-80, 2009.
  • 7. Chen G L, Sun G Z, and Xu Y, “Integrated research
  • of parallel computing: Status and future,” Chinese
  • Sci Bull, vol. 54(11), pp. 1845¯1853, 2009.
  • 8. Granma A, Gupta A, and Karypis G, “Introduction
  • to parallel computing,” Boston: Benjaming/
  • Cummings Publish Company, Inc., 2003
  • 9. Intel® Threading Building Blocks Tutorial, pp. 27.
  • 10. Yaming Li, “Computer organization and
  • architecture,” Tsinghua University Press, pp. 334-
  • 341, 2000(4).
  • 11. Focai Peng, Cuihong Han, and Yongrui Zhang,
  • Shuqun Shen, and Eryuan Zhao, “Research on
  • Instruction Parallelism-based Software Pipeline,”
  • Microelectronics and Computer, vol. 20(12), pp.
  • 1-3, 2003.