Video encoder optimization via evolutionary multiobjective optimization algorithms

Authors:
Alvaro Luis Bustamante;José M. Molina López;Miguel A. Patricio
Affiliations:
Universidad Carlos III de Madrid, Madrid, Spain;Universidad Carlos III de Madrid, Madrid, Spain;Universidad Carlos III de Madrid, Madrid, Spain
Venue:
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Year:
2009

Citing 3
Cited 1

Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

MIJ2K: Enhanced video transmission based on conditional replenishment of JPEG2000 tiles with motion compensation

Journal of Visual Communication and Image Representation

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Abstract

This paper deals with the multi-objective definition of video compression and it solving using the NSGA-II algorithm. We define the video compression as a problem including two competing objectives and we try to find a set of near-optimal solutions so called Pareto-optimal solutions instead of a single optimal solution. This will be applied to a new codec that is patent pending, which needs some optimizations before it release. The compression is achieved over a standard video, commonly used for video performance measurement. Also we present the NSGA-II convergence speed and discuss the suitability of MOEAs in this scope.