基于区域分割梯度直方图保持的地震信号去噪

Seismic Signal Denoising Based on Region Segmentation Gradient Histogram Preservation

在采集地震信号时可能会伴随着随机噪声,有些去噪算法会平滑掉地震信号中的部分细节,从而降低地震数据的准确性。为此提出了一种基于区域分割梯度直方图保持(SGHP)的地震信号去噪算法,该算法先将地震含噪信号分成几个区域,再估计每个区域的参考梯度直方图,最后对每个区域使用梯度直方图保持进行去噪,使得去噪后的地震信号的梯度分布尽可能接近原始信号,从而达到保护地震信号细节的目的。利用SGHP分别对合成地震信号和叠后陆上地震信号进行去噪,与非局部均值滤波(NLM)、块匹配三维(BM3D)协同滤波和聚类稀疏表示(CSR)的去噪效果进行对比,采用峰值信噪比和结构相似度的评价指标进行评估,结果表明,SGHP的去噪效果最优。

Random noise may accompany the acquisition of seismic signals,and some denoising algorithms can smoothen some of the details in seismic signals,which will result in reduction in seismic data accuracy.In this study,a seismic signal denoising algorithm based on region segmentation gradient histogram preservation(SGHP)is proposed.The proposed algorithm first divides the seismic noise signal into several regions,then estimates the reference gradient histogram for each region.Finally,each region is denoised using gradient histogram preservation so that the gradient distribution of the denoised seismic signal is as close as possible to that of the original signal,achieving the purpose of protecting the details of the seismic signal.SGHP is used to denoise the synthesized seismic signals and post-stack land seismic signals,and is compared with non-local mean filtering(NLM),block matching3 D(BM3 D)cooperative filtering,and clustering sparse representation(CSR)algorithms for denoising effect through evaluation indicators such as peak signal to noise ratio and structural similarities.Results show that SGHP has an optimal denoising effect.