Seismic interferometry is widely used to image and monitor earth structures at different scales by extracting an empirical Green’s function (EGF) from the crosscorrelation of ambient noise under the assumption of diffuse wavefields or energy equipartitioning. However, EGFs may be incorrectly estimated and lead to a misunderstanding of subsurface structures because the distribution of ambient noise sources is neither isotropic nor stationary. To extract reliable EGFs from the nonideal ambient noise data, we develop a polarization-based azimuth filter (PAF) to attenuate the ambient noise energy of nonstationary sources to improve the quality of crosscorrelation functions. The PAF is a time-frequency domain azimuth filter for 3C seismic data, which uses time-frequency polarization analysis to measure the azimuths of ambient noise signals and then filters the 3C data to obtain the signals from desired directions. Based on the stationary-phase theory, we use the PAF to extract the ambient noise signals from stationary-phase zones, which improves the quality of the crosscorrelation function and eliminates the requirement for long observations. A synthetic test and two short-time engineering examples demonstrate that uneven source distributions might cause serious spurious signals in EGFs, and we demonstrate the improvement in EGFs using our method. In addition, the PAF may allow for the complete separation of the fundamental and higher modes of Rayleigh waves, which uncovers more information implicit in the ambient noise data.