Abstract
The bilateral filter is an edge-preserving smoothing filter to reduce the superimposed noise on a signal. The tuning of smoothing parameters in the bilateral filter using an input signal is needed to produce a good reconstructed one. The difference between the input and reconstructed signals is regarded as a noise component. If the similarity between the estimated noise distribution and the assumed noise distribution model is high, it will be expected that a good reconstructed signal is given. In the proposed method, the similarity is calculated using the Hellinger distance and the smoothing parameters in the bilateral filter are tuned based on it.
