Edge detection and location of seismic image based on PCNN

The discontinuous features in seismic data usually correspond to different geological edge information. Effective processing of these seismic data can help us make correct geological interpretations. In this paper, we apply coherent slices to detect and locate the boundary of fault polygons and propose a method for boundary detection and localization of seismic images based on PCNN. In image edge detection, the basic PCNN needs to adjust many parameters. This paper aims at this problem to improve the basic PCNN model, we simplify the feedback input and pulse input, only retain the external input stimulation and the connection domain external neuron stimulation, reduce the parameters, and simplify the calculation. Optimize parameters such as internal activity link coefficients, dynamic thresholds, and cycle times to improve interpretation efficiency and accuracy. Experiments show that the method used in this paper has good practicability and can effectively realize the fault polygons detection and positioning of coherent slices.