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基于非下采样shearlet变换的微地震资料去噪方法,相比于其他多尺度变换方法具有更好的方向敏感性和最优稀疏表示性能,具有更强的去除随机噪声的能力,信号保真度更好。同时较传统的shearlet变换具有平移不变性,克服了伪吉布斯现象。利用非下采样shearlet变换阈值去噪法与小波和曲波阈值变换方法对微地震仿真和实际资料的随机噪声的压制进行对比分析,结果表明非下采样shearlet变换具有更好的去噪能力。
The microseismic data denoising method based on nonsubsampled shearlet transform has better direction sensitivity and optimal sparse representation performance than other multi-scale transform methods, and has better capability of removing random noise, and the signal fidelity better. At the same time, the traditional shearlet transform has the invariance of translation and overcomes the pseudo-Gibbs phenomenon. The non-subsampled shearlet transform threshold de-noising method and the wavelet and curvelet threshold transform method are used to compare the microseismic simulation and the actual data random noise suppression. The results show that the non-subsampled shearlet transform has better denoising ability.