Thus it's quite common to get better performing impulse noise filters with model-based systems, which are programmed with the time and frequency properties of the noise to remove only impulse obliterated samples.
Model-based systems for impulse noise filtering often yield superior performance compared to traditional methods. These systems are designed to target only those samples corrupted by impulsive events, effectively removing them from the data.