A new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative for potential field data

边察觉和改进技术通常在用潜在的域数据认出地质的身体的边被使用。我们在场一种新边识别技术基于有边察觉和改进技术的功能的全部的水平衍生物的规范的垂直衍生物。首先，我们计算潜在地的数据的全部的水平衍生物(THDR ) 然后计算 n 顺序 THDR 的垂直衍生物(VDRn ) 。为 n 顺序垂直衍生物，全部的水平衍生物(PTHDR ) 的山峰价值用比 0 大的阀值价值被获得。这 PTHDR 能被用于边察觉。第二， PTHDR 价值被全部的水平衍生物划分并且由最大的价值使正常化。最后，我们使用了数字模型的不同类型验证新边识别技术的有效性和可靠性。

Edge detection and enhancement techniques are commonly used in recognizing the edge of geologic bodies using potential field data. We present a new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative which has the functions of both edge detection and enhancement techniques. First, we calculate the total horizontal derivative （THDR） of the potential-field data and then compute the n-order vertical derivative （VDRn） of the THDR. For the n-order vertical derivative, the peak value of total horizontal derivative （PTHDR） is obtained using a threshold value greater than 0. This PTHDR can be used for edge detection. Second, the PTHDR value is divided by the total horizontal derivative and normalized by the maximum value. Finally, we used different kinds of numerical models to verify the effectiveness and reliability of the new edge recognition technology.