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Universal Denoising of Continuous Amplitude Signals with Applications to Images

机译:普遍去噪与图像的应用程序的连续幅度信号

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We consider the problem of image denoising wherein the statistical characterization of the noise corruption mechanism is known. We make no assumptions on the nature or statistics of the underlying noise-free signal. A denoiser is proposed which, although ignorant of the statistical properties of the noise-free image, does essentially as well as a scheme with full knowledge of the statistics. The solution is presented as a sequence of schemes that progressively consider larger neighborhoods (contexts) around a pixel being denoised, to achieve optimum performance under a user-defined distortion measure
机译:我们考虑了图像去噪的问题,其中已知噪声损坏机制的统计表征。 我们对潜在无噪声信号的性质或统计没有假设。 提出了一种脱落器,但是虽然无噪声图像的统计特性无知,但基本上以及具有全面了解统计数据的方案。 该解决方案作为一系列方案呈现,该方案逐步考虑围绕被解析的像素围绕像素的较大邻域(上下文),以在用户定义的失真度量下实现最佳性能

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