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Invariant wavelet packets for noise reduction on quasi-periodic structures

机译:不变小波包,用于降噪对准周期性结构

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We address the question of noise reduction on images of very low SNR that predominantly contain quasiperiodic image features. In this case neither the Fourier transform nor wavelet transforms are appropriate signal representations that allow for discrimination of signal and noise in the tranform domain. We show the construction of a multidimensional,cycle-spinning based, translation- and rotation-invariant waelet packet transform and employ this transform is a scheme for denoising data with an unknown spectral signal-noise relationship. We compare the signal reconstruction performance with that of other noise reduction methods. The proposed scheme allows for data exploration on low-SNR imagery of the given type.
机译:我们解决了极低的SNR图像的降噪问题,这些图像主要包含QuaSiodic图像特征。在这种情况下,傅立叶变换和小波变换都不是适当的信号表示,其允许判断Tranform域中的信号和噪声。我们展示了基于多维,循环旋转的,翻译和旋转不变的织印分组变换的构造,并且采用该变换是用于以未知的频谱信号噪声关系去噪的方案。我们将信号重建性能与其他降噪方法的信号进行比较。所提出的方案允许对给定类型的低SNR图像进行数据探索。

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