重力张量数据的目标体边缘检测方法探讨

Discussion on the edge detection technique for gravity gradient tensor data

文中介绍了几种目前常用的利用位场数据提取目标体边界的算法。通过分析各种边界提取算法的结果特征,将其分为阶跃型边缘和屋脊型边缘两种,并把边缘检测技术应用到重力张量数据处理中,利用阶跃型边缘检测算子和屋脊型边缘检测算子直接提取目标体边界。模型实验结果表明,利用边缘检测算法得到的目标体边界与实际边界吻合较好,与利用极值点、零点或其他特征点的边界提取算法相比,通过边缘检测算法得到的目标体边界更为精确、完整。同时通过对理论模型添加5%的高斯白噪声,证明了边缘检测算法具有一定的抗干扰能力。

There are a few algorithms commonly used for the edge extraction of potential data at present.By analyzing results of these edge extraction algorithms,we divide them into two types,viz.the step edge and the roof edge,and introduce the edge detection technique to data processing of gravity gradient tensor.Target boundaries are extracted directly by the step edge extraction algorithm and the roof edge extraction algorithm.The model experiments show that the target edge extracted by the edge detection algorithm is consistent with the real boundary very well.Comparing with previous boundary extraction algorithms,the new edge detection technique is more precise and continuous.By adding 5% Gaussian white noise to theoretical model,we prove that the edge detection algorithm has certain anti-interference ability.