Low-complexity and energy efficient image compression scheme for wireless sensor networks

  • Authors:

  • Qin Lu;Wusheng Luo;Jidong Wang;Bo Chen

  • Affiliations:

  • Department of Instrument Science and Technology, College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China;Department of Instrument Science and Technology, College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China;Department of Instrument Science and Technology, College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China;Department of Mathematic and System Science, College of Science, National University of Defense Technology, Changsha 410073, China

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2008

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Abstract

Currently most energy-constrained wireless sensor networks are designed with the object of minimizing the communication power at the cost of more computation. To achieve high compression efficiency, the main image compression algorithms used in wireless sensor networks are the high-complexity, state-of-the-art image compression standards, such as JPEG2000. These algorithms require complex hardware and make the energy consumption for computation comparable to communication energy dissipation. To reduce the hardware cost and the energy consumption of the sensor network, a low-complexity and energy efficient image compression scheme is proposed. The compression algorithm in the proposed scheme greatly lowers the computational complexity and reduces the required memory, while it still achieves required PSNR. The proposed implementation scheme of the image compression algorithm overcomes the computation and energy limitation of individual nodes by sharing the processing of tasks. And, it applies transmission range adjustment to save communication energy dissipation. Performance of the proposed scheme is investigated with respect to image quality and energy consumption. Simulation results show that it greatly prolongs the lifetime of the network under a specific image quality requirement.