Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper

-

July Edition 2021

International Journal of Applied Information Systems solicits high quality original research papers for the July 2021 Edition of the journal. The last date of research paper submission is June 15, 2021.

Image Compression in Wireless sensor networks- A survey

M.sheik Dawood, L. Ahila, S. Sadasivam Published in

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
Info Co-published with IJCA
10.5120/ijais12-450227
Download full text
  1. M.sheik Dawood, L.ahila and S.sadasivam. Article: Image Compression in Wireless sensor networks- A survey. International Journal of Applied Information Systems 1(9):11-15, April 2012. BibTeX

    @article{key:article,
    	author = "M.sheik Dawood and L.ahila and S.sadasivam",
    	title = "Article: Image Compression in Wireless sensor networks- A survey",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 1,
    	number = 9,
    	pages = "11-15",
    	month = "April",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Wireless Sensor networks are battery powered due to which their lifetime is precisely limited. In this type of network the nodes commonly have very limited resources in terms of processing power, bandwidth and energy. Efficient coding of the multimedia content is therefore important. One possible way of achieve maximum utilization of those resource is applying compression on sensor event Usually, processing data consumes much less power than transmitting data in wireless medium, so it is effective to apply compression before transmitting data for reducing total power consumption by a sensor node. In this paper various energy efficient image compression techniques Collaborative image transmission using Sobal edge-detection, JPEG2000 image compression, Image Subtraction with Quantization of image; Adaptive Compression and Spatial Correlation-Based Image Compression are discussed.

Reference

  1. D. Culler, D. Estrin, and M. Srivastava. 2004. "Guest Editors' Introduction: Overview of Sensor Network," Computer, Volume: 37 Issue: 8, pp. 41-49.
  2. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. 2002. "A survey on sensor networks," IEEE Communications Magazine, Vol 40 Issue: 8.
  3. M. I. Razzak, S. A. Hussain, Abid Ali Minhas and Muhammad Sher. 2010. "Collaborative Image Compression in Wireless Sensor Networks," in Int. Journal of Computational Cognition, Vol. 8, No. 1.
  4. Huaming Wu and Alhussein A. Abouzeid, "Energy Efficient Distributed JPEG2000 Image Compression in Multihop Wireless Networks,"Applications and Services in Wireless Networks, 2004.
  5. S. A. Hussain, M. I. Razzak, A. A. Minhas, M. Sher and G. R Tahir. 2009. "Energy Efficient Image Compression in Wireless Sensor Networks," in International Journal of Recent Trends in Engineering, Vol. 2, No. 1.
  6. R. Wagner, R. Nowak, and R. Baraniuk. 2003, "Distributed image compression for sensor networks using correspondence analysis and super-resolution," in Proceedings of IEEE ICIP'03, volume 1, pages 597–600, Barcelona, Spain.
  7. George Nikolakopoulos, DionisisKandris, Anthony Tzes. 2010. "Adaptive Compression of Slowly Varying Images Transmitted over Wireless Sensor Networks," Sensors journal, Vol 10,pages 7170-7191
  8. Yi-Chen Tsai, Ming-Sui Lee, MeiyinShen and C. -C. Jay Kuo, . 2006. "A quad-tree decomposition approach to cartoon image compression," IEEE International Workshop on Multimedia Signal Processing (MMSP).
  9. Pu Wang, Rui Dai, Ian F. Akyildiz. 2011. "A Spatial Correlation-Based Image Compression Framework forWireless Multimedia Sensor Networks," IEEE Transactions on Multimedia, Vol. 13, NO. 2.

Keywords

: Image Compression, Energy Efficiency, Sensor Network