改进光流算法在地震图像纹理分析的应用研究

To effectively protect the linear structure of seismic image while eliminating noise, a new method which combines improved optical flow algorithm with texture smoothing filter was proposed. First, the multiple-scale description method of Gauss pyramid was used to solve the problem of large flow velocity calculation and improve its accuracy. Secondly, by setting the threshold value of the mean square root for the residual error of the iteration results, the number of iterations was reduced and the processing time was shortened. Finally, according to the texture complexity of seismic profile image and combined with texture attribute analysis, different templates were selected for texture smoothing filtering to improve the signal-to-noise ratio (SNR). Compared with the conventional median filter and some advanced algorithms such as the improved Sobel filter and the Normalized Full Gradient method for seismic image boundary detection, the proposed algorithm could effectively preserve the edge information of seismic data, and enhance the continuity of seismic image in-phase axis. In particular, the SNR was increased by 7~10 dB, and the processing time was shortened by 2~3 minutes. Experimental results show that by combining the Gauss pyramid multiple-scale description with the optical flow algorithm and the texture smoothing filtering, the texture structure and energy of the original image could be well preserved by the integrated improved algorithm proposed in this paper. Meanwhile, the SNR was enhanced and the processing time was reduced. Therefore, the efficiency of seismic data interpretation was improved, indicating that the proposed algorithm is a better processing method in the field of seismic image texture analysis.