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  • 标题:Shift Invariance Level Comparison of Several Contourlet Transforms and Their Texture Image Retrieval Systems
  • 本地全文:下载
  • 作者:Xinwu Chen ; Jingjing Xue ; Zhen Liu
  • 期刊名称:Journal of Signal and Information Processing
  • 印刷版ISSN:2159-4465
  • 电子版ISSN:2159-4481
  • 出版年度:2016
  • 卷号:07
  • 期号:01
  • 页码:1-6
  • DOI:10.4236/jsip.2016.71001
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:In this paper, we proposed a metric to measure the shift invariance of the three different contourlet transforms. And then, using the same structure texture image retrieval system which use subband coefficients energy, standard deviation and kurtosis features with Canberra distance, we gave a comparison of their texture description abilities. Experimental results show that contourlet-2.3 texture image retrieval system has almost retrieval rates with non-sub sampled contourlet system; the two systems have better retrieval results than the original contourlet retrieval system. On the other hand, for the relatively lower redundancy, we recommend using contourlet- 2.3 as texture description transform.
  • 关键词:Content Based Texture Image Retrieval;Shift Invariance Level;Contourlet Transform;Contourlet-2.3
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