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Suprathreshold stochastic resonance and maximizing network for watermark detection

机译:超阈值随机共振和最大化水印检测网络

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摘要

We propose a novel method that improves watermark detection performance, based on suprathreshold stochastic reso nance (SSR) with a maximizing network. The detection pertormance is measured in terms of correlation. The proposed method has been tested on different gray-scale images, and we found that an original image is not required for watermark detectbn, so this method is blind. We improved the correlation between an original watermark and the SSR with maximizing network-based discrete wavelet trans form coefficients of the watermarked image. Our experimental results have been compared with the different existing techniques and were found superior in terms of correlation and ratio of correlation to thresh old.
机译:我们提出了一种基于超阈值随机共振(SSR)和最大化网络的水印检测性能改进方法。根据相关性测量检测性能。该方法已经在不同的灰度图像上进行了测试,发现水印检测不需要原始图像,因此该方法是盲目的。通过最大化水印图像的基于网络的离散小波变换系数,我们改善了原始水印与SSR之间的相关性。我们的实验结果已经与现有的不同技术进行了比较,并且在相关性和相关性与脱粒率的关系方面均表现出色。

著录项

  • 来源
    《Journal of electronic imaging》 |2012年第1期|p.013001.1-013001.9|共9页
  • 作者单位

    Indian Institute of Information Technology Jabalpur, 482001, India;

    Indian Institute of Technology Kharagpur, 721 302, India;

    Indian Institute of Information Technology Jabalpur, 482001, India;

    Indian Institute of Information Technology Jabalpur, 482001, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 01:17:43

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