Fast encoding method of vector quantization based on optimal subvector partition

Zhibin Pan, Koji Kotani, Tadahiro Ohmi

研究成果: Conference contribution

抄録

The encoding process of vector quantization (VQ) is very expensive computationally. By using the statistical features of the sum and the variance of a k-D whole vector, IEENNS method has been proposed to reject unlikely codewords. To further enhance the performance of IEENNS method, by first partitioning a k-D whole vector in half to generate its two (k/2)-D fixed subvectors and then directly applying IEENNS method once again to each subvector, a completeversion C-SIEENNS method and a simplified-version S-SIEENNS method have been proposed. By offline sorting the elements of a codeword before subvector partition, an adaptive A-SIEENNS method has been reported recently as well. However, there is no guarantee that these subvector partition methods are optimal. Thus, this paper proposes a practical criterion to optimally partition a k-D whole vector into a k1-D first subvector and a k2-D second subvector (k1+k2=k) by maximizing the energy included in the two partial sums of a codeword. Experimental results confirmed that this work can improve search efficiency significantly compared to the latest A-SIEENNS method

本文言語English
ホスト出版物のタイトル2007 15th International Conference on Digital Signal Processing, DSP 2007
ページ415-418
ページ数4
DOI
出版ステータスPublished - 2007 12 1
イベント2007 15th International Conference onDigital Signal Processing, DSP 2007 - Wales, United Kingdom
継続期間: 2007 7 12007 7 4

出版物シリーズ

名前2007 15th International Conference on Digital Signal Processing, DSP 2007

Other

Other2007 15th International Conference onDigital Signal Processing, DSP 2007
CountryUnited Kingdom
CityWales
Period07/7/107/7/4

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

フィンガープリント 「Fast encoding method of vector quantization based on optimal subvector partition」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル