A Pel-Recursive Wiener-Based Algorithm For The Simultaneous Estimation Of Rotation And Translation

Abstract

In this paper we derive a pel-recursive Wiener-based algorithm for the estimation of rotation and translation parameters in consecutive frames of an image sequence. The estimator minimizes the transformed frame difference (tfd) and the derivation is based on a Linearization of this tfd and a Wiener solution of the resulting stochastic linear observation equations. The use of a causal window and a segmentation algorithm allow the algorithm to work in a pet-recursive coding environment. Experiments on synthetic transformed data show that the algorithm is capable of estimating the motion parameters. Experiments on real coding data show a little gain in coding efficiency compared with existing pet-recursive displacement estimators. However, performance can be improved by a better segmentation algorithm and by taking into account the effect of motion boundaries.© (1988) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.