Weighted small subdomain filtering technology

A high-resolution method to define the horizontal edges of gravity sources is presented by improving the three-directional small subdomain filtering (TDSSF). This proposed method is the weighted small subdomain filtering (WSSF). The WSSF uses a numerical difference instead of the phase conversion in the TDSSF to reduce the computational complexity. To make the WSSF more insensitive to noise, the numerical difference is combined with the average algorithm. Unlike the TDSSF, the WSSF uses a weighted sum to integrate the numerical difference results along four directions into one contour, for making its interpretation more convenient and accurate. The locations of tightened gradient belts are used to define the edges of sources in the WSSF result. This proposed method is tested on synthetic data. The test results show that the WSSF provides the horizontal edges of sources more clearly and correctly, even if the sources are interfered with one another and the data is corrupted with random noise. Finally, the WSSF and two other known methods are applied to a real data respectively. The detected edges by the WSSF are sharper and more accurate.