Low Complexity Weighted Two-Bit Transforms Based Multiple Candidates Motion Estimation Exploiting the Redundant Computations

Author

Choi, Changryoul ; Jeong, Jechang

Author_Institution

Dept. of Electron. & Comput. Eng., Hanyang Univ., Seoul, South Korea

fYear

2010

fDate

7-10 Aug. 2010

Firstpage

101

Lastpage

104

Abstract

A low complexity weighted two-bit transforms (2BT) based multiple candidates motion estimation algorithm is proposed in this paper. By exploiting almost the identical operations in two different matching error criteria, we can efficiently determine two best motion vectors according to the respective matching criteria and can enhance the overall motion estimation accuracy. Experimental results show that the proposed algorithm achieves peak-to-peak signal-to-noise ratio (PSNR) gains about 0.47dB on average compared with the conventional 2BT-based motion estimation.

Keywords

image matching; motion estimation; signal processing; transforms; vectors; PSNR gains; low complexity weighted two-bit transforms; matching criteria; matching error criteria; motion estimation accuracy; motion vectors; multiple candidates motion estimation algorithm; peak-to-peak signal-to-noise ratio gains; redundant computations; Accuracy; Algorithm design and analysis; Artificial neural networks; Complexity theory; Motion estimation; PSNR; Transforms; block matching; full-search; motion estimation; two-bit transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Graphics, Imaging and Visualization (CGIV), 2010 Seventh International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-1-4244-7840-8

Type

conf

DOI

10.1109/CGIV.2010.23

Filename

5576196