Rapid Manipulation Method for Massive Remote Sensing Images Based on LRU Algorithm

Article Preview

Abstract:

With the rapid development of remote sensing (RS) technology, RS image data is growing larger and larger, which makes general image manipulation method limited in feasibility, speed and efficiency. In this paper, a rapid manipulation method of massive RS data based on Least Recently Used (LRU) algorithm in operating system page scheduling is proposed. Its core content includes data read-write based on memory mapping, data organization based on image pyramid with layers and blocks and caching based on LRU algorithm. The experiment shows that this method can greatly increase the speed and efficiency of massive RS images processing.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

826-831

Citation:

Online since:

January 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] J.S. Vitter, External Memory Algorithms and Data Structures: Dealing with Massive Data, ACM Computing Surveys, vol. 33, no. 2, pp.214-220, (2001).

DOI: 10.1145/384192.384193

Google Scholar

[2] L.Y. Zhang, R.R. Zhou, and L.S. Zhou, Model Reconstruction From Cloud Data For Rapid Prototype Manufacturing, Transactions of Nanjing University of Aeronautics & Astronautics, (2001).

Google Scholar

[3] W.Z. Hu, N. Liu, and R.Y. Liu, Quick-read Means for Large Scale Images Based on Storage Mapping File Technique, Application Research of Computers, vol. 22, no. 2, pp.111-112, (2005).

Google Scholar

[4] J.H. Song and Z.M. Zhao, Application of Tile and Hierarchy Structure in Massive Image Processing, Computer Engineering and Applications, vol. 40, no. 33, pp.31-33, (2004).

Google Scholar

[5] S.B. Xu and W.J. Guo, Study and Discussion on Reading Method of File with Large Pictures, Computer Applications and Software, vol. 26, no. 6, pp.126-140, (2009).

Google Scholar

[6] N.X. Yang, C.Q. Zhu, and A.L. Nie, Memory-mapped Files and It's Application on Fast Read/Write from Mass Data Files, Application Research of Computers, vol. 21, no. 8, pp.187-188, (2004).

Google Scholar

[7] J.G. Lu, G.M. Huang, and M.H. Yang, On Implement Fast Access of Large Quantities of Data by Visual C++, Science of Surveying and Mapping, vol. 27, no. 3, pp.29-32, (2002).

Google Scholar

[8] X.C. Zhang, Z.C. Huang, G. Chen, H.X. Jiang, and Y.H. Pan, Rapid Display Technique of Massive Remote Sensing Image, Journal of Image and Graphics, vol. 7(A), no. 10, pp.1021-1026, (2002).

Google Scholar

[9] Y. Xu and G.L. Wan, Technology of displaying mass data image in real time, Computer Engneering and design, vol. 24, no. 6, pp.36-38, (2003).

Google Scholar

[10] F.X. Yu, G.X. Wang, and G. Wan, Rapid Allocation and Display of Massive Remote Sensing Image, Hydrographic Surveying and Charting, vol. 26, no. 2, pp.27-30, (2006).

Google Scholar

[11] D. Cline and P.K. Egbert, Interactive Display Of Very Large Textures, IEEE, pp.343-350, (1998).

Google Scholar

[12] Y.H. Deng, J.L. Zhang, and D. Feng, Research on the Virtual Storage Pool of Mass Storage System, MNI-MICRO SYSTEMS, vol. 25, no. 9, pp.1574-1577, (2004).

Google Scholar

[13] B.X. Guo, J.L. Zhang, and Z.C. Zhang, Algorithm of Spatial Data Scheduling Based on Memory Pool, Computer Engineering, vol. 34, no. 6, pp.63-64, (2008).

Google Scholar

[14] D.R. Jones, E.R. Jurrus, and B.D. Moon, Gi gapixel-size Real-time Interactive Image Processing with Parallel Computers, International Parallel and Distributed Processing Symposium, France, April (2003).

DOI: 10.1109/ipdps.2003.1213426

Google Scholar