Approximating boundaries of causative sources is an important task in potential field interpretation. Many techniques have been proposed for approximating the edges including derivative and phase-based methods. The derivative-based methods cannot equalize the signal amplitudes, and although the phase-based methods do not have this problem, they maybe produce false edges, or the obtained edges are diffused. To overcome these problems, the ridges of some edge detection functions can be determined using the algorithms such as the Blakely and Simpson's algorithm or the curvature analysis algorithm. However, these algorithms cannot fully identify all the peaks of the data or produce some spurious ridges in output maps. In this study, we introduce an improved method to locate the peaks of the data. The efficiency of the algorithm is demonstrated on two synthetic gravity data, as well as real gravity data of the Vredefort dome area (South Africa). Compared with two traditional methods, the proposed algorithm produces more precise and detailed results.

使潜在原因的边界接近是潜在领域解释中的重要任务。已经提出了许多用于近似边缘的技术，包括基于导数和基于相位的方法。基于导数的方法无法均衡信号幅度，尽管基于相位的方法不存在此问题，但它们可能会产生伪边缘，或者会分散获得的边缘。为了克服这些问题，可以使用诸如布雷克利和辛普森算法或曲率分析算法之类的算法来确定某些边缘检测函数的脊。但是，这些算法无法完全识别数据的所有峰值或在输出映射中产生一些虚假的脊。在这项研究中，我们介绍了一种改进的方法来定位数据的峰值。在两个合成重力数据以及Vredefort穹顶区域（南非）的实际重力数据上证明了该算法的效率。与两种传统方法相比，该算法产生了更加精确和详细的结果。