Title :
A Novel Framework for Multi-objective Optimization of Video CODECs
Author :
Al-Abri, F. ; Li, X. ; Edirisinghe, E.A. ; Grecos, C.
Author_Institution :
Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
Abstract :
In this paper we propose a novel framework for the multi-objective optimization of a video codec based on genetic algorithms. The proposed framework is designed to jointly minimize the complexity, memory usage (both at the encoder and decoder), bit rate and to maximize the quality of the compressed video stream. In particular, in our present attempt the optimization strategy is designed to determine the optimum coding parameters for a H.264 AVC video codec in a memory and bandwidth constrained environment. This is demonstrated through extensive experiments and mathematical formulation that results in the optimum solution/s to the multi-objective optimisation problem being found. We show that such an approach is highly desirable in obtaining optimum coding parameters for video delivery over the Internet, where a feedback channel from the decoder to the encoder is practical.
Keywords :
Internet; computational complexity; data compression; decoding; genetic algorithms; image sequences; minimisation; video codecs; video coding; video streaming; H.264 AVC video codec; Internet; bandwidth constrained environment; computational complexity minimization; decoder; encoder; feedback channel; genetic algorithm; mathematical formulation; memory utilization; multiobjective optimization framework; optimum coding parameter; video sequence; video stream compression; Automatic voltage control; Bandwidth; Bit rate; Constraint optimization; Decoding; Design optimization; Genetic algorithms; Streaming media; Video codecs; Video compression; Multi-objective optimization; video coding;
Conference_Titel :
CyberWorlds, 2009. CW '09. International Conference on
Conference_Location :
Bradford
Print_ISBN :
978-1-4244-4864-7
Electronic_ISBN :
978-0-7695-3791-7