Denoising events camera data by overlapping multiple encoded channels

We present an opto-algorithmic method for removing noise from event data captured by event cameras. This method distinguishes between co-occurring signal events transmitted through multiple optical channels and uncorrelated noise events. We demonstrate the technique by splitting the optical image into two spatially encoding channels and overlapping these channels on the event camera sensor. As a result, the co-occurring events can be separated from the noise events. Our opto-algorithmic method is agnostic to the type of background activity noise and shows improved performance compared to purely algorithmic approaches.