Performance Improvement of Vector Quantization by Using Threshold

  • Hung-Yi Chang
  • Pi-Chung Wang
  • Rong-Chang Chen
  • Shuo-Cheng Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3333)

Abstract

Vector quantization (VQ) is an elementary technique for image compression. However, the complexity of searching the nearest codeword in a codebook is time-consuming. In this work, we improve the performance of VQ by adopting the concept of THRESHOLD. Our concept utilizes the positional information to represent the geometric relation within codewords. With the new concept, the lookup procedure only need to calculate Euclidean distance for codewords which are within the threshold, thus sifts candidate codewords easily. Our scheme is simple and suitable for hardware implementation. Moreover, the scheme is a plug-in which can cooperate with existing schemes to further fasten search speed. The effectiveness of the proposed scheme is further demonstrated through experiments. In the experimental results, the proposed scheme can reduce 64% computation with only an extra storage of 512 bytes.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Hung-Yi Chang
    • 1
  • Pi-Chung Wang
    • 2
  • Rong-Chang Chen
    • 3
  • Shuo-Cheng Hu
    • 4
  1. 1.Department of Information ManagementI-Shou UniversityTa-Hsu Hsiang, Kaohsiung CountyTaiwan, R.O.C.
  2. 2.Institute of Computer Science and Information TechnologyNational Taichung Institute of TechnologyTaichungTaiwan, R.O.C.
  3. 3.Department of Logistics Engineering and ManagementNational Taichung Institute of TechnologyTaichungTaiwan, R.O.C.
  4. 4.Department of Information ManagementMing-Hsin University of Science and TechnologyHsinchuTaiwan, R.O.C.

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