MIJ2K Optimization using evolutionary multiobjective optimization algorithms

► MOEAs are used in a video compression optimization. ► Quality and compression ratio are presented as competing objectives. ► Five decision variables or internal codec parameters are optimized simultaneously. ► A near-optimal Pareto front is obtained with the best compressions found. ► A fast conve...

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Vydané v:Expert systems with applications Ročník 38; číslo 9; s. 10999 - 11010
Hlavní autori: Bustamante, Alvaro Luis, Molina López, José M., Patricio, Miguel A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.09.2011
Predmet:
Algorithms
Codec
Coders
Convergence
Encoder
Encoders
Maximization
Multi-objective
Optimization
Video
Video compression
Multi-objective
Video
Encoder
Optimization
ISSN:0957-4174, 1873-6793
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Shrnutí:► MOEAs are used in a video compression optimization. ► Quality and compression ratio are presented as competing objectives. ► Five decision variables or internal codec parameters are optimized simultaneously. ► A near-optimal Pareto front is obtained with the best compressions found. ► A fast convergence speed is achieved with the use of MOEAs. This paper deals with the multiobjective definition of video compression and its optimization. The optimization will be done using NSGA-II, a well-tested and highly accurate algorithm with a high convergence speed developed for solving multiobjective problems. Video compression is defined as a problem including two competing objectives. We try to find a set of optimal, so-called Pareto-optimal solutions, instead of a single optimal solution. The two competing objectives are quality and compression ratio maximization. The optimization will be achieved using a new patent pending codec, called MIJ2K, also outlined in this paper. Video will be compressed with the MIJ2K codec applied to some classical videos used for performance measurement, selected from the Xiph.org Foundation repository. The result of the optimization will be a set of near-optimal encoder parameters. We also present the convergence of NSGA-II with different encoder parameters and discuss the suitability of MOEAs as opposed to classical search-based techniques in this field.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2011.02.143