High-resolution reflection seismics is a powerful tool that can provide the required resolution for subsurface imaging and monitoring in urban settings. Shallow seismic reflection data acquired in soil-covered sites are often contaminated by source-coherent surface waves and other linear moveout noises (LMON) that might be caused by, e.g., anthropogenic sources or harmonic distortion in vibroseis data. In the case of shear-wave seismic reflection data, such noises are particularly problematic as they overlap the useful shallow reflections. We have developed new schemes for suppressing such surface-wave noise and LMON while still preserving shallow reflections, which are of great interest to high-resolution near-surface imaging. We do this by making use of two techniques. First, we make use of seismic interferometry to retrieve predominantly source-coherent surface waves and LMON. We then adaptively subtract these dominant source-coherent surface waves and LMON from the seismic data in a separate step. We illustrate our proposed method using synthetic and field data. We compare results from our method with results from frequency–wave-number (f-k) filtering. Using synthetic data, we show that our schemes are robust in separating shallow reflections from source-coherent surface waves and LMON even when they share very similar velocity and frequency contents, whereas f-k filtering might cause undesirable artefacts. Using a field shear-wave reflection dataset characterised by overwhelming LMON, we show that the reflectors at a very shallow depth can be imaged because of significant suppression of the LMON due to the application of the scheme that we have developed.