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首页> 外文会议>2002 6th International Conference on Signal Processing Proceedings (ICSP'02) Vol.2; Aug 26-30, 2002; Beijing, China >Embodying Information into Images By an MMI-Based Independent Component Analysis Algorithm
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Embodying Information into Images By an MMI-Based Independent Component Analysis Algorithm

机译：通过基于MMI的独立成分分析算法将信息体现在图像中

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摘要

The signals measured by multi-sensors are always the mixtures of several independent sources. Therefore, it is necessary to separate them from each other for practical applications. Independent component analysis is a novel signal processing method presented in dealing with such problems. Recently, it is also found very useful in many other problems such as biomedical signal separation, communication and multimedia information processing. In this paper, we gave a minimizing mutual information based ICA algorithm and then applied it into information hiding or digital watermarks. We consider the original image as a mixture of some independent character images. So we can embodying the watermark into the separated images and then remix them as a watermarked image. Simulations results show the validity in embodying information into images.
机译：多传感器测量的信号始终是几种独立信号源的混合。因此，在实际应用中有必要将它们彼此分开。独立分量分析是解决此类问题提出的一种新颖的信号处理方法。最近，还发现它在许多其他问题中非常有用，例如生物医学信号分离，通信和多媒体信息处理。在本文中，我们给出了基于互信息最小化的ICA算法，然后将其应用于信息隐藏或数字水印中。我们认为原始图像是一些独立字符图像的混合。因此，我们可以将水印包含在分离的图像中，然后将它们重新混合为水印图像。仿真结果表明了将信息体现在图像中的有效性。

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