Adaptive filtering of color noise using the Kalman filter algorithm
In the view of the drawbacks of the conventional Kalman filtering, a kind of adaptive Kalman filtering approach of color noise based on the correlative method of the system output is proposed. This approach builds the Kalman filtering model of color noise by adopting the equivalent measurement equation in order to avoid complicated computation and the expansion of the dimension of the filter. It is unnecessary to know the variance of the measurement noise beforehand so that it is closer to the actual situation. The correlative method of the system output is presented to estimate the variance of the measurement noise. The adaptive filtering of color noise using the Kalman filter algorithm is applied to solve the cephalometric images of stomatology. Several experimental results demonstrate the feasibility and good performance of the approach.