Enhancing the detection accuracy of the edges of the geological features within the subsurface remains a significant objective in geophysical data interpretation. Despite numerous advancements, approaches stemming from the directional gradients of gravity and magnetic fields still grapple with challenges such as low-resolution outcomes and susceptibility to noise contamination. In this study, we introduce a novel filtering framework based on the total horizontal gradient and its derivatives, designed to yield more precise and coherent edges free from false boundaries or disruptive artifacts. Validation using synthetic Bishop complex magnetic and gravity datasets, alongside Tuangiao aeromagnetic data from Vietnam, substantiates the robustness and applicability of our modified approach. Furthermore, recognizing the inherent susceptibility of edge detection filters to noise contamination resulting from directional derivatives, we employ the recently developed modified non-local means (MNLM) algorithm to alleviate noise effects prior to the analysis of noisy synthetic and real datasets. Our findings confirm the efficacy of the proposed method in reducing false artifacts and identifying edges with heightened precision, positioning MHGA as a valuable alternative for processing potential field data.

Gravity anomaly maps often contain spatially overlapping signatures from numerous sources, each with varying shapes, depths, and density contrasts. Locating these signatures using edge detection techniques is crucial for geological structural interpretation and imaging of horizontal boundaries. This paper proposes two effective edge detection tools: one combining the balanced total horizontal gradient (BHG), and the hyperbolic tangent function, abbreviated as “MTBHG”; and the other combining the tilt angle of the total horizontal gradient (TAHG) and the hyperbolic tangent function, abbreviated as “MTAHG.” Additionally, the Modified Non‐Local Means (MNLM) filter was applied to suppress possible noise effects amplified by the gradient calculation process. Synthetic tests validated that the MTAHG and MTBHG detectors outperform other representative detectors. Two high‐resolution gravity data sets from the Western Carpathians in Slovakia and the Witwatersrand Basin in South Africa were used to test the applicability of the modified methods. Results show that the modified detectors achieve superior edge delineation and avoid creating spurious anomalies or artifacts even in the presence of unwanted noise interference. Furthermore, by eliminating false tilt‐depth (TD) solutions via the edge detection results, we enhance the accuracy of depth estimates and facilitate the credible identification of both horizontal and vertical structure distributions.

Structural edge detection in gravity and magnetic data is fundamental for constraining subsurface architecture in complex tectonic settings. Yet widely used derivative- and phase-based filters still face a trade-off between resolution, stability, and noise sensitivity. In this study, we introduce a new edge-enhancement operator, the Bi-Hyperbolic Tilt (BiHT) filter, which combines directional derivatives of the Total Horizontal Derivative (THDR) with a bidirectional hyperbolic tangent transformation. The method applies dual $$\tanh$$ tanh functions to the x and y components of the THDR, and uses a $$\beta$$ β -Vertical Derivative ( $$\beta$$ β -VDR) stabilization step to sharpen lateral contrasts while suppressing noise-induced artifacts. We evaluate the performance of BiHT through four synthetic experiments designed to span both gravity and magnetic data and to represent noise-free and noisy survey conditions. Comparative analyses against seven established filters (THDR, AS, TDR, TDX, TDTH, THSTDR, THiTDX) show that BiHT consistently produces sharper, more geologically coherent edges with reduced false boundary generation and improved depth continuity, particularly in noisy datasets. The method is further tested on aeromagnetic data from the Seattle Uplift region in western Washington, USA. Here, BiHT delineates the main structural trends associated with the Seattle Fault Zone and the Tacoma Fault more clearly than conventional filters do. When combined with tilt-angle depth estimation, it yields source depths that are consistent with previous geophysical interpretations. These results indicate that BiHT is a robust and adaptable tool for structural interpretation of potential-field data. It offers a practical balance between edge resolution and complements existing derivative- and phase-based approaches.

Potential field data play a critical role in interpreting various geologic structural features through edge detection filters that aid in mapping subsurface structural features. For this purpose, various filters have been introduced in recent years to determine lateral boundaries. However, each of these filters has its limitations and advantages. This study presents a new edge enhancement filter named “Enhanced Gradient (EG)” based on the Richards function and applies it to potential field data for structural mapping. The EG is tested on two dimensional (2D) and three dimensional (3D) synthetic magnetic models with sources buried at different depths and variable properties. The results from the EG filter provide more accurate and higher resolution horizontal boundaries and can avoid creating the false edges in the output results. In addition, the proposed filter was examined using aeromagnetic data from the Indiana region in the USA. The primary and secondary faults and geological formations are recognizable in the EG image. The results of the EG map will allow us to improve the qualitative interpretation of potential field anomalies in studying the structural and tectonic geology of the Indiana region in the USA.