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Image and Its Noise Removal in Nakagami Fading Channels

机译:纳克马褪色渠道中的图像及其噪声清除

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A maximum likelihood for Bayesian estimator based on α-stable was discussed in our previous papers. It is in terms of closer to a realistic situation, and unlike previous methods used for Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The Bayesian estimator here is based on in a Nakagami fading channel. Our previous research results has been extended to that Bayesian estimator that we investigated is still working well for the image noise removal in Nakagami fading channels. As an example, an improved Bayesian estimator (soft and hard threshold methods), is illustrated in our discussion.
机译:在我们之前的论文中讨论了基于α-稳定的贝叶斯估计的最大可能性。它根据更接近逼真的情况,与以前用于贝叶斯估计器的方法不同,对于这里讨论的情况,这里没有必要知道噪声的方差。这里的贝叶斯估计者是基于Nakagami衰落通道。我们以前的研究结果已经扩展到我们调查的贝叶斯估计人员仍然在纳克马伊褪色渠道中的图像噪声去除工作。作为示例,我们的讨论中示出了改进的贝叶斯估计器(软硬阈值方法)。

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