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Stimulated Raman scattering (SRS) microscopy is an important non-linear optical technique for the investigation of unlabeled samples. The SRS signal manifests itself as a small intensity exchange between the laser pulses involved in coherent excitation of Raman modes. Usually, high-frequency modulation is applied in one pulse train, and the signal is then detected on the other pulse train via lock-in amplification. While allowing shot-noise limited detection sensitivity, lock-in detection, which corresponds to filtering the signal in the frequency domain, is not the most efficient way of using the excitation light. In this manuscript, we show that boxcar averaging, which is equivalent to temporal filtering, is better suited for the detection of low-duty-cycle signals as encountered in SRS microscopy. We demonstrate that by employing suitable gating windows, the signal-to-noise ratios achievable with lock-in detection can be realized in shorter time with boxcar averaging. Therefore, high-quality images are recorded at a faster rate and lower irradiance which is an important factor, e.g., for minimizing degradation of biological samples.Stimulated Raman scattering (SRS) microscopy is an important non-linear optical technique for the investigation of unlabeled samples. The SRS signal manifests itself as a small intensity exchange between the laser pulses involved in coherent excitation of Raman modes. Usually, high-frequency modulation is applied in one pulse train, and the signal is then detected on the other pulse train via lock-in amplification. While allowing shot-noise limited detection sensitivity, lock-in detection, which corresponds to filtering the signal in the frequency domain, is not the most efficient way of using the excitation light. In this manuscript, we show that boxcar averaging, which is equivalent to temporal filtering, is better suited for the detection of low-duty-cycle signals as encountered in SRS microscopy. We demonstrate that by employing suitable gating windows, the signal-to-noise ratios achievable with lock-in detection can be realized in shorter time with boxcar averaging. Therefore, high-quality images are...