Performance analysis of vector quantizer for imaging data clustering algorithms

Ting-Wei Hou, Houng Kuo Ku, Yuan Tsung Chen, Horng Show Koo

Research output: Contribution to conferencePaperpeer-review


Generalized Lloyd Algorithm(GLA) is the most famous known algorithm technique in the field of vector quantizer design. It runs very fast, but it can only find a poor local optimum in most cases. In 1989, Zeger proposed the Stochastic Relaxation Decoder(SRD) algorithm to overcome the weakness of the GLA. Theoretically, it has the ability to find the global optimum. In practice, it can achieve the near optimal performance. We proposed an improved approach named Codebook Reorganization Algorithm(CRA), for the vector quantizer design. The performance of CRA is superior to the above-mentioned algorithms demonstrated by the experimental results. It can find better codebooks than GLA. It also can find a codebook as good as SRD in less time.

Original languageEnglish
Number of pages2
Publication statusPublished - 2006 Dec 1
Event13th International Display Workshops, IDW '06 - Otsu, Japan
Duration: 2006 Dec 62006 Dec 6


Other13th International Display Workshops, IDW '06

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Radiology Nuclear Medicine and imaging
  • Atomic and Molecular Physics, and Optics

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