Advertisement

Image Quality Estimation in Wireless Multimedia Sensor Networks: An Experimental Study

  • Pinar Sarisaray Boluk
  • Kerem Irgan
  • Sebnem Baydere
  • A. Emre Harmanci
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 66)

Abstract

Multimedia applications in wireless sensor networks (WMSN) have stringent quality of service (QoS) requirements. In this paper, we study image quality distortions due to packet losses in multi hop WMSN. An experimental simulation and real testbed environment has been setup to estimate the quality of the test images over 30,000 transmissions. Two scenarios are considered: in the first scenario, images are watermarked with their replicas at the source node and an error concealment (EC) algorithm is employed at the sink. In the second scenario, raw images are transmitted without any encoding. The empirical results have revealed that there is a strong correlation between Peak-Signal-To-Noise-Ratio (PSNR) values of the distorted images and packet loss rate of the transmission route (PER). Moreover, the relationship is linear when EC technique is used with an achievement over 25dB PSNR for PER less than 0.6. This correlation is useful when designing QoS based transport schemes.

Keywords

Image Transmission Wireless Multimedia Sensor Networks WSN TestBed PSNR Estimation Error Concealment Watermarking 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Akyildiz, I., Melodia, T., Chowdhury, K.: A survey on wireless multimedia sensor networks. Computer Networks 51, 92–960 (2007)Google Scholar
  2. 2.
    Chow, K., Lui, K., Lam, E.: Efficient Selective Image Transmission in Visual Sensor Networks. In: IEEE 65th VTC, pp. 1–5 (2007)Google Scholar
  3. 3.
    Chen, M., Leung, V., Mao, S., Yuan, Y.: Directional geographical routing for real-time video communications in wireless sensor networks. Computer Communications 30, 3368–3383 (2007)CrossRefGoogle Scholar
  4. 4.
    Dai, R., Akyildiz, I.F.: A spatial correlation model for visual information in wireless multimedia sensor networks. Trans. Multi. 11, 1148–1159 (2009)CrossRefGoogle Scholar
  5. 5.
    Lee, H., Tessens, L., Morbee, M., Aghajan, H., Philips, W.: Sub-optimal Camera Selection in Practical Vision Networks through Shape Approximation. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2008. LNCS, vol. 5259, pp. 266–277. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    Barr, K., Asanovic, K.: Energy-aware lossless data compression. ACM Transactions on Computer Systems (TOCS) 24, 291 (2006)CrossRefGoogle Scholar
  7. 7.
    Wu, H., Abouzeid, A.: Energy efficient distributed JPEG2000 image compression in multihop wireless networks. In: IEEE ASWN, Citeseer, pp. 152–160 (2004)Google Scholar
  8. 8.
    Lee, D., Kim, H., Rahimi, M., Estrin, D., Villasenor, J.: Energy-efficient image compression for resource-constrained platforms. IEEE Transactions on Image Processing 18 (2009)Google Scholar
  9. 9.
    Pekhteryev, G., Sahinoglu, Z., Orlik, P., Bhatti, G.: Image transmission over IEEE 802.15. 4 and ZigBee networks. In: IEEE ISCAS, pp. 3539–3542 (2005)Google Scholar
  10. 10.
    Wu, H., Abouzeid, A.: Power aware image transmission in energy constrained wireless networks. In: ISCC, pp. 202–207 (2004)Google Scholar
  11. 11.
    Ferrigno, L., Marano, S., Paciello, V., Pietrosanto, A.: Balancing computational and transmission power consumption in wireless image sensor networks. In: IEEE VECIMS, p. 6 (2005)Google Scholar
  12. 12.
    Lin, S., Costello, D.: Error control coding: fundamentals and applications. Prenticehall, Englewood Cliffs (1983)zbMATHGoogle Scholar
  13. 13.
    Zorzi, M.: Performance of FEC and ARQ error control in bursty channels underdelay constraints. In: 48th IEEE VTC, vol. 2 (1998)Google Scholar
  14. 14.
    Thomos, N., Boulgouris, N., Strintzis, M.: Optimized transmission of JPEG2000 streams over wireless channels. IEEE Transactions on Image Processing 15, 54–67 (2006)CrossRefGoogle Scholar
  15. 15.
    Zhu, Q., Wang, Y.: Error Control and Concealment for Video Communication. In: Visual Information Representation, Communication, and Image Processing (1999)Google Scholar
  16. 16.
    Sarisaray, P., Gur, G., Baydere, S., Harmanc, E.: Performance Comparison of Error Compensation Techniques with Multipath Transmission in Wireless Multimedia Sensor Networks. In: 15th MASCOTS, pp. 73–86 (2007)Google Scholar
  17. 17.
    Kundur, D., Hatzinakos, D.: Digital watermarking for telltale tamper proofing and authentication. Proceedings of the IEEE 87, 1167–1180 (1999)CrossRefGoogle Scholar
  18. 18.
    Kundur, D., Hatzinakos, D.: Toward robust logo watermarking using multiresolution image fusion principles. IEEE Transactions on Multimedia 6, 185–198 (2004)CrossRefGoogle Scholar
  19. 19.
    Zuniga, M., Krishnamachari, B.: An analysis of unreliability and asymmetry in low-power wireless links. ACM Transactions on Sensor Networks (TOSN) 3, 7 (2007)CrossRefGoogle Scholar
  20. 20.
    Crossbow, T.: TelosB Data Sheet, http://www.xbow.com/
  21. 21.
    Department, U.B.E.: TinyOS: An operating system for sensor networks, http://www.tinyos.net/

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Pinar Sarisaray Boluk
    • 1
  • Kerem Irgan
    • 2
  • Sebnem Baydere
    • 2
  • A. Emre Harmanci
    • 1
  1. 1.Istanbul Technical UniversityIstanbulTurkey
  2. 2.Yeditepe UniversityIstanbulTurkey

Personalised recommendations