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文章基本信息

  • 标题:Exposing Image Sharpen Forgeries Based on Dyadic Contrast Contourlet
  • 本地全文:下载
  • 作者:Hua Zhen ; Li Jinjiang
  • 期刊名称:International Journal of Multimedia and Ubiquitous Engineering
  • 印刷版ISSN:1975-0080
  • 出版年度:2015
  • 卷号:10
  • 期号:7
  • 页码:237-246
  • DOI:10.14257/ijmue.2015.10.7.25
  • 出版社:SERSC
  • 摘要:In order to distinguish the sharpening operation in a manipulated image, a sharpen forgeries detection algorithm is proposed. Combined with efficient image signal processing method, a new non-subsampled dyadic contourlet transform based on contrast à trous wavelet is designed. In contourlet domain, sharpening characteristics are analyzed by multi-scale and multi-directional methods. A classifier is trained by artificial intelligence methods to complete sharpening tampered image detection. Experimental results show that the algorithm in this paper can detect possible sharpening and locate the tampering boundary accurately.
  • 关键词:sharpened operation; image tampering; dyadic contourlet; contrast à trous ; wavelet
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