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Coherent noise removal in seismic data with dual-tree M-band wavelets

机译:利用双树M波段小波消除地震数据中的相干噪声

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Seismic data and their complexity still challenge signal processing algorithms in several applications. The advent of wavelet transforms has allowed improvements in tackling denoising problems. We propose here coherent noise filtering in seismic data with the dual-tree M-band wavelet transform. They offer the possibility to decompose data locally with improved multiscale directions and frequency bands. Denoising is performed in a deterministic fashion in the directional subbands, depending of the coherent noise properties. Preliminary results show that they consistently better preserve seismic signal of interest embedded in highly energetic directional noises than discrete critically sampled and redundant separable wavelet transforms.
机译:地震数据及其复杂性仍然挑战着几种应用中的信号处理算法。小波变换的出现允许改进解决降噪问题。我们在这里提出用双树M带小波变换对地震数据进行相干噪声滤波。它们提供了使用改进的多尺度方向和频带在本地分解数据的可能性。取决于相干噪声特性,在方向性子带中以确定性方式执行降噪。初步结果表明,与离散的临界采样和冗余的可分离小波变换相比,它们始终可以更好地保留嵌入高能方向性噪声中的目标地震信号。

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