Vania Vieira Estrela, Nikolas P. Galatsanos, Vania Vieira Estrela, Nikolas P. Galatsanos, Vania Vieira Estrela, Vânia Estrela, Vania Vieira Estrela, Vânia Vieira Estrela, Vania Vieira Estrela, Nikolas P. Galatsanos, Nikolas P. Galatsanos, Nikolaos Galatsanos. Spatially Adaptive Regularized Pel-Recursive Motion Estimation Based on the EM Algorithm. 2000. [doi]
Pel-recursive motion estimation is a well-established approach for motion estimation. However, in the presence of noise, it becomes an il-posed problem that requires regulation. In the past, regularization for pel-recursive estimations was addressed in an ad-hoc manner. In this paper, a Bayesian estimation framework is used to deal with this issue. More specifically, motion vectors and regularization parameters are estimated in an iterative fashion by means of the Expectation- Maximization (EM) algorithm and a Gaussian data model. The proposed algorithm utilizes the local image properties to regularize the motion vector estimates following a spatially adaptive approach. Numerical experiments are presented that demonstrate the merits of the proposed algorithm.