Abstract
The paper deals with parallel large aerospace images processing. We considered a simple multi-alternative discrete accumulation method for reliable distinction of satellite imagery and implemented a parallel classification system to increase the algorithm efficiency. The process of development of the distinction algorithm and system architecture was described. The system prototype was successfully tested. The experiments allowed to draw conclusion about the system performance and to estimate the effect of using the parallel architecture. The considered approach could be used in complex neural networks processing.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bartelev, S.A., Lupyan, E.A.: Research and works of ISR RAS on satellite monitoring of the vegetative cover. Mod. Probl. Earth Studying Space 10, 197–214 (2013)
Terentyev, I.V.: Reliable object recognition on the aerospace images of the surface. Study Studying Earth Space 5, 57–64 (1999)
Jensen, J.R.: Introductory Digital Image Processing, 3rd edn. Prentice Hall, Upper Saddle River (2005)
Yao, W., Zeng, Z., Lian, C., Tang, H.: A kernel ELM classifier for high-resolution remotely sensed imagery based on multiple features. In: Zeng, Z., Li, Y., King, I. (eds.) ISNN 2014. LNCS, vol. 8866, pp. 270–277. Springer, Heidelberg (2014)
Potapov, A.S.: Principle of representational minimum description length in image analysis and pattern recognition. Pattern Recogn. Image Anal. 22, 82–91 (2012)
Jia, S., Liu, H., Sun, F.: Aerial scene classification with convolutional neural networks. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds.) ISNN 2015. LNCS, vol. 9377, pp. 258–265. Springer, Heidelberg (2015). doi:10.1007/978-3-319-25393-0_29
Berezin, V.I., Vorobiev, V.I., Vasiliev, N.P., Morus, G.A., Terentyev, I.V., Shubina, M.A.: Reliable distinction of forestry objects. Earth Studying Space 4, 55–62 (2003)
Shapiro, L., Stockman, G.: Computer Vision. Moscow, Binom (2006)
Zubkov, I.A., Skripachev, V.O.: Application of unsupervised classification algorithms to process the earth remote sounding data. In: The 4th Russian Open Conference “Modern Problems of the Earth Studying from Space” (2006)
Terentyev, I.V.: Distinction of separate hand-written symbols by means of optimization techniques. Comput. Model. 2005, 407–408 (2005)
Gropp, W., Hoefler, T., Thakur, R., Lusk, E.: Modern Features of the Message-Passing Interface. The MIT Press, Cambridge (2014)
MPI: A Message-Passing Interface Standard. Message Passing Interface Forum. http://www.mpi-forum.org/docs/mpi-3.0/mpi30-report.pdf
Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Elements of Reusable Object-Elemented Software. Design Patterns. St. Petersburg, Piter (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Vorobiev, V.I., Evnevich, E.L., Levonevskiy, D.K. (2016). Parallel Classification of Large Aerospace Images by the Multi-alternative Discrete Accumulation Method. In: Cheng, L., Liu, Q., Ronzhin, A. (eds) Advances in Neural Networks – ISNN 2016. ISNN 2016. Lecture Notes in Computer Science(), vol 9719. Springer, Cham. https://doi.org/10.1007/978-3-319-40663-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-40663-3_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40662-6
Online ISBN: 978-3-319-40663-3
eBook Packages: Computer ScienceComputer Science (R0)