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  • 标题:フラクタル画像符号化におけるGAを用いたIFSパラメータの量子化法
  • 本地全文:下载
  • 作者:竹沢 恵 ; 長谷山 美紀 ; 北島 秀夫
  • 期刊名称:映像情報メディア学会誌
  • 印刷版ISSN:1342-6907
  • 电子版ISSN:1881-6908
  • 出版年度:2002
  • 卷号:56
  • 期号:10
  • 页码:1633-1642
  • DOI:10.3169/itej.56.1633
  • 出版社:The Institute of Image Information and Television Engineers
  • 摘要:This paper proposes a high-accuracy quantization method for IFS parameters in fractal image coding by using genetic algorithms (GA). The development of IFS-parameter quantization methods is significant for image coding because quantization errors have a negative influence on reconstructed image quality. The conventional method quantizes the IFS parameters to the nearest possible values and thus minimizes the quantization errors. However, it does not necessarily minimize the errors in images reconstructed from an original. Therefore, a new quantization method which minimizes that error is proposed. The proposed method consists of two GAs; because if a simple GA searches for the optimal quantization-parameter set, it converges to local optima because of the complexity of the search space. Experimental results verify that the proposed method can effectively find the optimal quantization-parameter set and provide high-quality reconstructed images.
  • 关键词:フラクタル画像符号化;IFSパラメータ;量子化;遺伝的アルゴリズム (GA)
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