Quantization parameter cascading for video coding: leveraging a new temporal distortion propagation model

Abstract

In video coder, inter-frame prediction causes distortion propagation among temporally adjacent frames. This distortion dependency is a crucial factor for rate control optimization. Quantization parameter cascading (QPC) is an efficient technique to achieve dependent rate distortion optimization (RDO). This paper proposes a general framework for temporal dependency analysis by leveraging a distortion propagation model, which is derived by employing window-based preanalysis on original frames. Then, a quantization parameter offset \(\delta \) model is proposed for achieving fine-granularity quantization control, according to the amount of distortion propagation measured by the relative propagation cost \(\rho \). This paper applies competitive decision in exploring \(\delta \)–\(\rho \) model as accurate as possible and then proposes an improved \(\delta \)–\(\rho \) model tailored for dependent RDO. The simulation results verify that the temporal QPC algorithm with the proposed model achieves up to 1.1–1.4 dB PSNR improvement, with smaller temporal distortion fluctuation contributed by efficient bit allocation.