In this study, a new adaptive morphological filter is developed based on the mathematical morphology algorithm and characteristics of the subtle differences in the waveform morphology in seismic data. The algorithm improves the traditional morphological dilation and corrosion operations. In this study, we propose a multiscale adaptive operator based on the principle of morphological structural “probes” and present the corresponding mathematical proof. Simulation experiments and actual seismic data processing results show that compared with traditional morphological filters, the constructed OCCO-based multistructure adaptive morphological filter can suppress noise to the greatest extent. Moreover, it can effectively improve the SNR of the images, and offers great application prospects.

本研究基于数学形态学算法和地震数据波形形态细微差异的特点，开发了一种新的自适应形态滤波器。该算法改进了传统的形态膨胀和腐蚀操作。在这项研究中，我们提出了一种基于形态结构“探针”原理的多尺度自适应算子，并给出了相应的数学证明。仿真实验和实际地震数据处理结果表明，与传统形态滤波器相比，构建的基于OCCO的多结构自适应形态滤波器能够最大程度地抑制噪声。而且，它可以有效地提高图像的信噪比，具有很好的应用前景。