Towards predictor, quantizer and entropy coder optimality in scalable video coding

Abstract

A novel coding paradigm is proposed to jointly optimize the prediction, quantization, and entropy coding modules, thereby approaching optimality in scalable video coding. It departs from conventional video coding schemes that consider prediction, transformation, quantization, and entropy coding, as largely separate sequential functional components. The method draws inspiration from an early estimation-theoretic approach, developed by our group for enhancement layer prediction, which efficiently combines all the information available to the enhancement layer coder, to produce the optimal prediction. The framework is significantly expanded here to also incorporate optimization of entropy-constrained quantization and arithmetic coding, while fully accounting for hitherto ignored relevant factors, inherent to predictive scalable coding, including information from the base layer quantization operation, and from the enhancement layer motion compensated reference. Experimental evidence is provided for substantial coding gains over conventional scalable video coding.