Edge detection is one of the most important steps in interpretation of magnetic and gravity data. In magnetic and gravity maps, it is difficult to distinguish adjacent sources due to their field superposition. Many different techniques have been used to determine the edges of sources. These techniques are based on vertical or horizontal gradients of magnetic and gravity data or combinations of them, and the edges of the geological structures are determined by maximum, minimum, or zero values in the output maps. One of the most popular techniques is the total horizontal gradient which is based on horizontal gradients of magnetic and gravity data. The capability of the total horizontal gradient technique in mapping the boundaries of deep bodies is very limited when competing with large-amplitude shallow bodies. Some enhanced modifications of the total horizontal gradient technique have been introduced to improve the boundary estimation results. These techniques are based on logistic functions and derivatives of the total horizontal gradient. In this study, we aim to estimate the effectiveness of the logistic filters of the total horizontal gradient. To obtain optimum results, these filters were tested on synthetic gravity and magnetic data and real magnetic data from the Zhurihe region (China). The findings show that the logistic filters can provide more accurate and sharper boundaries without false source edges than the total horizontal gradient. These techniques can determine the edges of shallow and deep structures at the same time. These results demonstrate that the logistic filters are useful tools for the qualitative interpretation of potential field data.