Efficient Filter for EEG Signal Using Non Local Mean Approach

Abstract

Non Local Mean (NLM) filter has attracted great attention within the images and signal processing field especially in the last ten years. The main contribution of this paper to the field of biomedical signals processing is introducing the straightforward application of the fast NLM filter to EEG signal contaminated with "Additive White Gaussian Noise" (AWGN). The performance of this filter is analysed by evaluating its optimal parameters. All the tests are conducted using actual EEG signal captured from human brain. The performance of this filter is determined using "Output Signal to Noise Ratio" (SNRo) and "Cross Correlation" (CC) criteria. The NLM filter exhibits excellent performance in rejection the AWGN from the EEG signal.