One-Sided $\rho$-GGD Source Modeling and Rate-Distortion Optimization in Scalable Wavelet Video Coder

Abstract

We develop an accurate source model, one-sided ρ-generalized Gaussian distribution (GGD), for approximating the residual signals in scalable wavelet video coding. An efficient piecewise linear expression is suggested to estimate the shape parameter of the one-sided ρ-GGD. We also improve the model accuracy in matching the real data by modifying the ρ parameter estimation formula. Continuing our previous work on developing the motion information gain metric to measure the motion information efficiency, we now incorporate the one-sided ρ -GGD model in the cost function, which is used for deciding the motion vectors and motion estimation mode in scalable wavelet video coding. Compared with the conventional Lagrangian optimization, our simulation results show that the new mode decision method generally improves the peak signal-to-noise ratio performance in the combined signal-to-noise ratio and temporal scalability cases.