Fractal Coding based Optimization Algorithm for Interframe Prediction of High-definition Video

DOI

10.2991/meici-18.2018.132How to use a DOI?

Keywords

Fractal coding; Inter-frame motion vector; HEVC

Abstract

A fractal coding based interframe prediction algorithm is proposed, to hugely reduce the calculation amount of interframe prediction and raise the coding velocity. The complexity of interframe prediction algorithm is the motion search. The interframe prediction in HEVC needs to find out the best matched block for each image block of each division mode of the current frame in the reference frame. The defining of the reference frame is also very complex, especially for the frame of bidirectional prediction, its reference frame needs to be defined on two directions, and then the best matched image block for the current image block in the reference frame is to be further defined. To cope this high complexity of interframe prediction, we make some improvements on the part of motion search for the interframe prediction by introducing the fractal idea to match the image block to realize more rapid matching of image block. The experimental result shows that the coding efficiency of fractal coding-based interframe prediction algorithm averagely improves by 7.86%, the peak SNR averagely reduces 0.164 dB and the coding time averagely reduces by 22.37%. The proposed algorithm can significantly raise the coding velocity and cut the coding time hardly with any influence on the coding quality.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chang Liu
PY  - 2018/12
DA  - 2018/12
TI  - Fractal Coding based Optimization Algorithm for Interframe Prediction of High-definition Video
BT  - Proceedings of the 2018 8th International Conference on Management, Education and Information (MEICI 2018)
PB  - Atlantis Press
SP  - 666
EP  - 670
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-18.2018.132
DO  - 10.2991/meici-18.2018.132
ID  - Liu2018/12
ER  -