DocumentCode
3148402
Title
Residual error curvature estimation and adaptive classification for selective sub-pel precision motion estimation
Author
Blasi, Saverio G. ; Izquierdo, Ebroul
Author_Institution
Sch. of Electron. Eng. & Comput. Sci., Queen Mary Univ. of London, London, UK
fYear
2012
fDate
25-30 March 2012
Firstpage
1193
Lastpage
1196
Abstract
We present a novel approach for adaptive precision motion estimation based on a classification of the residual error curvature. A fast algorithm is proposed to estimate the curvature of the interpolated residual surface using the error samples after integer precision motion estimation. We also propose an original technique to compute and successively update a set of thresholds using the information from previously coded frames. The optimal motion vector precision is then selected for each block according to the current thresholds. The approach is compared in terms of PSNR of the motion compensated reconstruction against conventional state of the art sub-pel motion estimation algorithms, and it is shown to efficiently reduce complexity and coding times of a typical video encoder with negligible effects on the prediction accuracy.
Keywords
image classification; interpolation; motion estimation; video coding; PSNR; adaptive classification; complexity reduction; error samples; integer precision motion estimation; interpolated residual surface; motion compensated reconstruction; optimal motion vector precision; residual error curvature; residual error curvature estimation; selective subpel precision motion estimation; video encoder; Accuracy; Complexity theory; Interpolation; Motion estimation; PSNR; Prediction algorithms; Video coding; Motion estimation; video coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location
Kyoto
ISSN
1520-6149
Print_ISBN
978-1-4673-0045-2
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2012.6288101
Filename
6288101
Link To Document