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 non-linear filtering problem. We present a state-space representation of the matching problem, and show how non-linear 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.