Wavelet filters in multi-resolution motion estimation

Author

Zan, Jinwen ; Swamy, M.N.S. ; Ahmad, M.O.

Author_Institution

Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada

Volume

2

fYear

2001

fDate

2001

Firstpage

1321

Abstract

The performance of various wavelets, including those known to be well suited for the coding of still images, are evaluated for the multi-resolution motion estimation of video sequences. The multi-resolution motion estimation scheme proposed by Zhang and Zafar (1992), which has been widely cited in the literature, is used as the simulation scheme in this study. The prediction mean square error (PMSE) in the wavelet transform coefficient domain is used in our study as the measure for prediction performance. In order to show the overall rate distortion performance, the number of bits needed to encode the motion vectors is also calculated. Simulation results show that the 7/9 biorthogonal wavelet, one of the best wavelets for the coding of still images, is the best wavelet for the task of multi-resolution motion estimation among the wavelets evaluated in this study

Keywords

filtering theory; image resolution; image sequences; mean square error methods; motion estimation; prediction theory; rate distortion theory; transform coding; video coding; wavelet transforms; biorthogonal wavelet; motion vector encoding; multiresolution motion estimation; prediction mean square error; prediction performance; rate distortion performance; simulation results; still image coding; video sequences; wavelet filters; wavelet transform coefficient; wavelets performance; Energy resolution; Filters; Fourier transforms; Frequency; Image coding; Motion estimation; Video sequences; Wavelet analysis; Wavelet domain; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2001. Canadian Conference on

Conference_Location

Toronto, Ont.

ISSN

0840-7789

Print_ISBN

0-7803-6715-4

Type

conf

DOI

10.1109/CCECE.2001.933637

Filename

933637