Adaptive filtering approach of color noise and its application in cephalometeric image

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