Single-View Information Reduction Techniques for WMSN Using Event Compression

  • Li-minn Ang
  • Kah Phooi Seng
  • Li Wern Chew
  • Lee Seng Yeong
  • Wai Chong Chia


This chapter presents single-view information reduction techniques using the set partitioning in hierarchical tree (SPIHT) image compression algorithm. An overview of image compression models using the first and second generation compression algorithms is first described followed by the description of the SPIHT algorithm. Modifications have been introduced on the traditional SPIHT image coding technique with the aim to provide a low-memory implementation of the SPIHT coder in a wireless multimedia sensor network (WMSN) as well as improving its compression performance. The proposed approach employs a strip-based processing technique where an image is partitioned into strips and each strip is encoded separately. Besides, it also uses the new one-dimensional memory-addressing method to store the wavelet coefficients at predetermined locations in the strip buffer for ease of coding. To further reduce the memory requirements, the proposed SPIHT coding employs a new spatial orientation tree (SOT) structure and a listless approach that allow for a very low-memory implementation of the strip-based image coding. In addition, a modification to the SPIHT algorithm by reintroducing the degree-0 zerotree coding methodology was used to give a high-compression performance. Simulations show that even though the proposed image compression architecture using strip-based processing requires a much less complex hardware implementation and its efficient memory organisation uses a lesser amount of embedded memory for processing and buffering, it can still achieve a very good compression performance. The chapter concludes with the hardware implementation of the modified SPIHT coder for low-memory implementation on the strip-based MIPS processor.


Discrete Cosine Transform Discrete Wavelet Transformation Wavelet Coefficient Discrete Cosine Transform Coefficient Joint Photographic Expert Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Li-minn Ang
    • 1
  • Kah Phooi Seng
    • 1
  • Li Wern Chew
    • 3
  • Lee Seng Yeong
    • 2
  • Wai Chong Chia
    • 2
  1. 1.School of EngineeringEdith Cowan UniversityJoondalupAustralia
  2. 2.Dept. of Computer Science and Networked SystemsSunway UniversitySelangorMalaysia
  3. 3.Intel Architecture GroupIntel CorporationPenangMalaysia

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