赵冲,李辉峰,赵驰,等. 基于地震波相似性的非局部均值滤波压制异常振幅噪音[J]. 海洋地质前沿,2021,37(3):60-65. DOI: 10.16028/j.1009-2722.2020.069
    引用本文: 赵冲,李辉峰,赵驰,等. 基于地震波相似性的非局部均值滤波压制异常振幅噪音[J]. 海洋地质前沿,2021,37(3):60-65. DOI: 10.16028/j.1009-2722.2020.069
    ZHAO Chong, LI Huifeng, ZHAO Chi, YANG Feilong, YANG Wenping, HUANG Dezhi, LUO Hao, ZHAO Xiu, ZHANG Xue. SUPPRESSION OF ABNORMAL AMPLITUDE NOISE WITH SEISMIC WAVE SIMILARITY NON-LOCAL MEAN FILTER[J]. Marine Geology Frontiers, 2021, 37(3): 60-65. DOI: 10.16028/j.1009-2722.2020.069
    Citation: ZHAO Chong, LI Huifeng, ZHAO Chi, YANG Feilong, YANG Wenping, HUANG Dezhi, LUO Hao, ZHAO Xiu, ZHANG Xue. SUPPRESSION OF ABNORMAL AMPLITUDE NOISE WITH SEISMIC WAVE SIMILARITY NON-LOCAL MEAN FILTER[J]. Marine Geology Frontiers, 2021, 37(3): 60-65. DOI: 10.16028/j.1009-2722.2020.069

    基于地震波相似性的非局部均值滤波压制异常振幅噪音

    SUPPRESSION OF ABNORMAL AMPLITUDE NOISE WITH SEISMIC WAVE SIMILARITY NON-LOCAL MEAN FILTER

    • 摘要: 非局部均值滤波是根据图像中各像素点间的相似性对图像进行去噪处理,但该方法不能有效压制图像中的异常振幅噪音。共偏移距道集(按炮点坐标排序的等炮检距道集)中同时刻的地震信号具有相似性高且分布范围集中的特征,因此可根据非局部均值滤波的权函数判断信号中的异常振幅噪音。基于上述理论,提出了基于地震波相似性的非局部均值滤波异常噪音压制方法,以有效地压制地震信号中的随机噪音与异常振幅噪音。该方法是在共偏移距道集中根据非局部均值滤波权函数来判断信号中的异常振幅噪音,并采用局部振幅统计估算对异常振幅噪音进行压制,从而达到去除地震信号中随机噪音和异常振幅噪音的目的。理论与实际地震数据试算结果表明,笔者所提出的方法可以有效地压制地震信号中的随机噪音和异常振幅噪音,可以让地震资料的信噪比得到进一步提高。

       

      Abstract: Non-local mean filtering denoises the image based on the similarity between pixels in the image. However, this method cannot effectively suppress the abnormal amplitude noise in the image. The seismic signals simultaneously in common offset gathers (equal offset gathers sorted by shot coordinates) have the characteristics of high similarity and concentrated distribution. So, the abnormal amplitude noise in the signal can be judged according to the weight function of non-local mean filtering. Based on the theory mentioned above, this paper proposes a non-local mean filtering method for suppressing abnormal noise based on the similarity of seismic waves to effectively suppress random noise and abnormal amplitude noise in seismic signals. The trial results of theoretical and actual seismic data show that the method proposed in this paper can effectively suppress random noise and abnormal amplitude noise in seismic signals, and can further improve the signal-to-noise ratio of seismic data.

       

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