Structural Prior-Guided Adaptive Wavelet Denoising for Single-Channel Dolphin Whistles

The continuous, narrowband time-frequency structure of dolphin whistles is an important information carrier for target detection, behavioral analysis, and ecological monitoring in passive acoustic monitoring. However, ocean noise can easily obscure whistle time-frequency contours, blur their boundaries, and cause local discontinuities, thereby reducing the reliability of subsequent acoustic analysis. Existing denoising methods based on transform-domain thresholding and spectral-domain statistical modeling can attenuate background interference to some extent. However, without explicit structural constraints, these methods still have difficulty achieving a satisfactory balance between noise suppression and preservation of the whistle time–frequency structure. To address this problem, this study proposes a Structural Prior-Guided Adaptive Wavelet Denoising (SPG-AWD) method for single-channel unsupervised scenarios. The proposed method introduces structural priors at two levels: adaptive subband selection and terminal node denoising. At the first level, subband nodes are adaptively split, retained, or suppressed based on stationary wavelet packet recursive decomposition and the distribution of candidate structures. At the second level, a structural mask satisfying local grouped-energy and two-dimensional time–frequency connectivity constraints is extracted, and a continuous whistle-presence probability is obtained through a signed distance transform. This probability is then used to jointly guide local noise power spectral density estimation and protective Wiener gain fusion. Simulation results show that, under real recorded background noise and ship noise conditions, SPG-AWD achieves favorable overall denoising performance when the input SNR is higher than −16 dB, while maintaining a more stable balance between target region energy preservation and non-target region noise suppression. Experiments on real recordings further demonstrate that the proposed method can effectively suppress in-band noise components within the whistle-bearing frequency range, better preserve continuous main frequency contours, and improve the overall perceptibility of whistle contours, confirming its applicability to single-channel dolphin whistle denoising in complex underwater noise environments.