Sorted evolutionary strategy based SOFM used for vector quantization

Ruirui Ji, Hong Zhu, Qieshi Zhang

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper presents a sorted evolutionary strategy based self-organizing feature map (SOFM) algorithm to improve the efficiency of vector quantization. The image samples are sorted according to the human vision sensitivity to ensure an optimal vision effect under the precondition of the globe minimum error. A similarity evaluation about code vector is introduced to the evolutionary algorithm to guarantee the variety of the code vector and the adaptability to the image. Experimental results show that the higher adaptability of codebook and better quality of reconstructed image.

本文言語English
ホスト出版物のタイトルProceedings of the 2004 International Conference on Information Acquisition, ICIA 2004
編集者T. Mei, M. Meng, Y. Ge, T.J. Tarn, Z. Wang, H. Szu
ページ331-334
ページ数4
出版ステータスPublished - 2004
外部発表はい
イベント2004 International Conference on Information Acquisition, ICIA 2004 - Hefei
継続期間: 2004 6 212004 6 25

Other

Other2004 International Conference on Information Acquisition, ICIA 2004
CityHefei
Period04/6/2104/6/25

ASJC Scopus subject areas

  • 工学(全般)

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