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

Phat Nguyen Huu, Vinh Tran-Quang, Takumi Miyoshi

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.

Original languageEnglish
Pages (from-to)3438-3447
Number of pages10
JournalIEICE Transactions on Communications
Issue number12
Publication statusPublished - 2010 Dec


  • Digital image processing
  • Discrete cosine transform
  • Energy balance
  • Lapped transform
  • Lempel-Ziv-Welch
  • Wireless sensor networks

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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