The receiver function (RF) is a widely used crustal imaging technique. In principle, it assumes relatively noise-free traces that can be used to target receiver-side structures following source deconvolution. In practice, however, mode conversions and reflections may be severely degraded by noisy conditions, hampering robust estimation of crustal parameters. In this study, we use a sparsity-promoting Radon transform to decompose the observed RF traces into their wavefield contributions, that is, direct conversions, multiples, and incoherent noise. By applying a crustal mask on the Radon-transformed RF, we obtain noise-free RF traces with only Moho conversions and reflections. We demonstrate, using a synthetic experiment and a real-data example from the Sierra Nevada, that our approach can effectively denoise the RFs and extract the underlying Moho signals. This greatly improves the robustness of crustal structure recovery as exemplified by subsequent H-k stacking. We further demonstrate, using a station sitting on loose sediments in the Upper Mississippi embayment, that a combination of our approach and frequency-domain filtering can significantly improve crustal imaging in reverberant settings. In the presence of complex crustal structures, for example, dipping Moho, intracrustal layers, and crustal anisotropy, we recommend caution when applying our proposed approach due to the difficulty of interpreting a possibly more complicated Radon image. We expect that our technique will enable high-resolution crustal imaging and inspire more applications of Radon transforms in seismic signal processing. [ABSTRACT FROM AUTHOR]