Sorted evolutionary strategy based SOFM used for vector quantization

Ruirui Ji, Hong Zhu, Qieshi Zhang

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

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.

元の言語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
出版物ステータスPublished - 2004
外部発表Yes
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
Hefei
期間04/6/2104/6/25

ASJC Scopus subject areas

  • Engineering(all)

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  • これを引用

    Ji, R., Zhu, H., & Zhang, Q. (2004). Sorted evolutionary strategy based SOFM used for vector quantization. : T. Mei, M. Meng, Y. Ge, T. J. Tarn, Z. Wang, & H. Szu (版), Proceedings of the 2004 International Conference on Information Acquisition, ICIA 2004 (pp. 331-334)