基于经验模态分解和混沌映射的秘密音频水印

Mehbooba P. Shareef, T. V. Divya
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引用次数: 1

摘要

数字水印已经在文献中讨论了几十年。从商业角度来看,它作为一种潜在的版权保护、所有权证明、广播监控等方法是很重要的。从学术角度来看,这是一个有趣的研究问题。音频水印是最具挑战性的,因为人类听觉系统对原始音频的微小变化都很敏感。除了信号的不可感知性外,容量和鲁棒性也很重要。经验模态分解是音频水印中最新的革命性概念。本文提出了一种鲁棒音频水印方案,该方案具有不可感知性、鲁棒性和高负载能力。为了防止未经授权的第三方删除水印,我们利用Tinkerbell混沌映射生成随机密钥,并在密钥后嵌入水印。采用多密钥保证水印的有效分发,防止裁剪攻击,实现水印的校正和与接收方的同步。实验结果表明,该方法对重采样、裁剪、重量化、AWGN攻击具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secret audio watermarking using empirical mode decomposition and chaotic map
Digital watermarking has been discussed in the literature for decades. In business perspective, it is important as a potential method for copy right protection, proof of ownership broadcast monitoring etc. In academic perspective, it is an interesting research problem. Audio watermarking is the most challenging of all as Human Auditory System is sensitive to even a very small change to the original audio. Other than imperceptibility of the signal, capacity and robustness are important too. Empirical mode decomposition is the latest revolutionary concept in audio watermarking. In this paper we present a robust audio watermarking scheme which ensures imperceptibility, robustness and high payload capacity. To prevent un-authorized third parties from removing the watermark, we make use of Tinkerbell chaotic map to generate random secret keys and watermark is embedded following the keys. Multiple keys are used to ensure efficient distribution of the watermark to prevent cropping attacks and enable watermark correction and synchronization with receiver. The experimental results show that the method is robust against re-sampling, cropping, re-quantization, AWGN attacks.
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