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Improved entropy of primitive for visual information estimation

  • Shurun Wang
  • , Zhenghui Zhao
  • , Xiang Zhang
  • , Jian Zhang
  • , Shiqi Wang
  • , Siwei Ma
  • , Wen Gao

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Sparse representation has been observed to be highly efficient in dealing with rich, varied and directional information in natural scenes. Based on the statistical analysis of primitives in sparse coding, the entropy of primitive (EoP) was proposed for measuring visual information of images, and its changing tendency has been shown to be highly relevant with the human visual system (HVS). But the sparse coefficient energy was ignored when calculating EoP, which may be critical in accounting for the primitive characteristics. To tackle this, an improved EoP is developed in this work via ℓ2 norm calculation. We further give mathematical derivations for its convergence verification. Experimental evaluations have also demonstrated that the improved EoP can achieve more stable convergence tendencies, which is consistent with the perceptual experiences.

源语言英语
主期刊名VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781509053162
DOI
出版状态已出版 - 4 1月 2017
已对外发布
活动2016 IEEE Visual Communication and Image Processing, VCIP 2016 - Chengdu, 中国
期限: 27 11月 201630 11月 2016

出版系列

姓名VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing

会议

会议2016 IEEE Visual Communication and Image Processing, VCIP 2016
国家/地区中国
Chengdu
时期27/11/1630/11/16

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