Locating seismic events is a central task for earthquake monitoring. Compared to arrival-based location methods, waveform-based location methods do not require picking phase arrivals and are more suitable for locating seismic events with noisy waveforms. Among waveform-based location methods, one approach is to stack different attributes of P and S waveforms around arrival times corresponding to potential event locations and origin times, and the maximum stacking values are assumed to indicate the correct event location and origin time. In this study, to obtain a high-resolution location image, we improve the waveform-based location method by applying a hybrid multiplicative imaging condition to characteristic functions of seismic waveforms. In our new stacking method, stations are divided into groups; characteristic functions of seismic waveforms recorded at stations in the same group are summed, and then multiplied among groups. We find that this approach can largely eliminate the cumulative effects of noise in the summation process and thus improve the resolution of location images. We test the new method and compare it to three other stacking methods, using both synthetic and real datasets that are related to induced seismicity occurring in petroleum/gas production. The test results confirm that the new stacking method can provide higher-resolution location images than those derived from currently used methods.