Simultaneous motion estimation and filtering of image sequences

Author

Fan, C.M. ; Namazi, N.M.

Author_Institution

Dept. of Electr. Eng., Catholic Univ. of America, Washington, DC, USA

Volume

2

fYear

1997

fDate

26-29 Oct 1997

Firstpage

156

Abstract

In this paper, we present an algorithm to simultaneously estimate multiple-frame motions and filter image sequences. The relative motion d _k(x) between the reference frame s(x) and the k^th frame s(x-d_k(x)) in the presence of additive white Gaussian noise (AWGN) are estimated using the maximum-likelihood (ML) principle. The reference frame is also filtered in the linear minimum mean square error (LMMSE) sense during the process of motion estimation. Simulation experiments are performed using the affine motion model to illustrate the performance of this method

Keywords

Gaussian noise; filtering theory; image sequences; least mean squares methods; maximum likelihood estimation; motion estimation; white noise; AWGN; additive white Gaussian noise; affine motion model; filtering; image sequences; linear minimum mean square error; maximum-likelihood principle; motion estimation; multiple-frame motions; reference frame; relative motion; simulation experiments; AWGN; Additive white noise; Covariance matrix; Filtering; Gaussian noise; Image sequences; Maximum likelihood estimation; Mean square error methods; Motion estimation; Nonlinear filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.638697

Filename

638697