A non-linear filtering approach to image matching

In this paper we present a novel approach to high precision stereo image matching which employs an iterated extended Kalman filter (IEKF). The matching problem is formulated as a nonlinear filtering problem. We present a state-space representation of the matching problem, and show how nonlinear filtering techniques may be applied to determine optimal transformation parameters. To demonstrate the efficacy of this approach we use an IEKF for matching one-dimensional pixel intensity profiles. The results indicate that the IEKF technique is capable of high accuracy and precision.