Sensor Signal Filtering for Low-Latency Noise Reduction

The patent applies a segmented filtering approach by processing the sensor signal in discrete time steps, where each output value is determined independently by comparing the current input value with previous and future input values. This segmentation allows real-time processing without the need for complex frequency domain transformations, thereby reducing signal latency while maintaining noise reduction capabilities.

The patent uses a look-ahead buffer to store future input values that are needed for the filtering calculation. By preparing and storing these values in advance, the system can perform the comparison and determination operations without waiting for future data to arrive, thus reducing the overall signal latency while still achieving effective noise filtering.

The patent applies local quality by treating different regions of the signal differently based on their characteristics. The filtering operation adapts locally by comparing each input value with its neighbors and determining the output based on the local pattern. This allows the filter to preserve sharp edges where they occur while still reducing noise in smoother regions, achieving both noise reduction and edge preservation simultaneously.

Instead of applying a conventional filter that smooths all regions uniformly, the patent inverts the approach by using the local variation pattern to determine the output. Rather than averaging or mediating all values, the method identifies and preserves significant local changes (edges) while filtering out noise, effectively doing the opposite of standard smoothing filters in terms of edge handling.