Frame-Based vs. Event-Based Optical Turbulence Strength Estimation: A Comparative and Hybrid Approach

Atmospheric turbulence, quantified by the refractive index structure parameter (Cn2), degrades the performance of optical systems. Reliable Cn2 estimation is critical for free-space optical communication, remote sensing, and astronomy. This study compares frame-based and event-based approaches to turbulence strength estimation. A high-speed CMOS camera (180/90/30 frames per second (FPS)) and an event camera were deployed along a 300 m outdoor path, with a scintillometer providing ground truth. Event streams were segmented into 5 s windows, features were extracted, and predictions were made using an Extreme Gradient Boosting regressor (XGBoost). A hybrid model was also tested, combining CMOS-based predictions with event features. Results show that CMOS accuracy is strongly dependent on frame rate, with diminishing returns beyond 90 FPS under weak turbulence. Event-based models achieved higher correlation with ground truth in strong turbulence but produced larger errors in weak regimes. The hybrid approach yielded the best overall performance in moderate-to-strong turbulence, reducing mean estimation error by ~35% compared to CMOS-only at 180 FPS. These findings demonstrate the complementary strengths of frame and event modalities. Frame cameras provide stability in weak turbulence, while event sensors capture fast fluctuations under stronger conditions. Together, they enable more robust Cn2 estimation and motivate further research into advanced hybrid sensing strategies for operational turbulence monitoring.