Lagrange multiplier selection in wavelet-based scalable video coding for quality scalability

Abstract

In this paper, a method for Lagrange multiplier selection is proposed in the context of rate-distortion optimisation for wavelet-based scalable video coding targeting quality scalability. Despite the prevalence of the conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to wavelet-based scalable video coding. To address the inherent challenges, a thorough analysis of the rate-distortion models for transform video coding is provided with regard to low and middle-to-high bit-rates, respectively. Based on the analysis, the models are consolidated according to experimental observations and the consolidated rate-distortion models serve as the basis for the derivation of the Lagrange multiplier. Considering the influence of the open-loop prediction structure on the rate-distortion performance, the Lagrange multiplier is initially derived for a single-targeted bit-rate. Moreover, the method for Lagrange multiplier selection in scalable video coding aiming at multiple-targeted bit-rates is proposed in a general sense of bit-rate range, varying from low to high bit-rates, building on the initially derived Lagrange multiplier for a single-targeted bit-rate. The proposed Lagrange multiplier is content adaptive and well suited for wavelet-based scalable video coding where quantisation steps are unavailable. Detailed performance evaluation of the proposed method for wavelet-based scalable video coding is provided with regard to a given targeted bit-rate and multiple-targeted bit-rates, respectively. The experimental results have demonstrated the effectiveness of the proposed Lagrange multiplier for rate-distortion optimisation considering quality scalability in wavelet-based scalable video coding.