Reduction of aeromagnetic noise and extraction of mineralization-related residual anomalies are critical for aeromagnetic data processing in mineral exploration. This study introduced a multifractal singular value decomposition (MSVD) method to remove the noise and improved the bi-dimensional empirical mode decomposition (BEMD) algorithm to extract residual magnetic anomalies. It is shown that MSVD and improved BEMD could effectively reduce the noise and extract residual magnetic anomalies. Then, a wavenumber–domain iterative approach is applied in 3D imaging of magnetic anomalies and gradients with depth constraints, which is a rapid tool for qualitative and quantitative interpretation of magnetic data and is suitable for rapidly imaging large-scale data. The 3D inversion result is verified by four geological sections along the regional tectonic directions and some drilling holes on the deposits. It is revealed that this proposed approach is practical and effective in dealing with aeromagnetic data interpretation and inversion for mineral exploration
