Seismic data denoising via shearlet transform and data‐driven tight frame
We propose a sort of double sparsity dictionary (DSD) to deal with random noise of seismic exploration, which consists of shearlet transform and data‐driven tight frame (DDTF). We train the DDTF dictionary in the domain of shearlet transform to improve the robustness of the dictionary. Furthermore, the function of hard‐thresholding is applied to find dictionary coefficients and cut small shearlet coefficients. Finally, we verified the reliability of the proposed approach by a synthetic data denoising example.
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Document Type: Research Article
Publication date: May 1, 2019