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Reallocation of GLA Codevectors for Evading Local Minimum

Timo Kaukoranta, Pasi Fränti, Olli Nevalainen, Reallocation of GLA Codevectors for Evading Local Minimum. TUCS Technical Reports 25, Turku Centre for Computer Science, 1996.

Abstract:

The performance of the Generalized Lloyd Algorithm (GLA) is improved by reallocating the codevectors every time GLA reaches a local optimum. This is done by splitting the largest partition and by merging two small neighboring partitions; thus preserving the size of the codebook. The whole procedure is repeated until no improvement is achieved.

<p>Contact authors for the complete report.

BibTeX entry:

@TECHREPORT{tKFN96,
  title = {Reallocation of GLA Codevectors for Evading Local Minimum},
  author = {Kaukoranta, Timo and Fränti, Pasi and Nevalainen, Olli},
  number = {25},
  series = {TUCS Technical Reports},
  publisher = {Turku Centre for Computer Science},
  year = {1996},
  keywords = {image compression, vector quantization, codebook generation},
  ISBN = {951-650-777-8},
}

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