Statistical model, analysis and approximation of rate-distortion function in MPEG-4 FGS videos

Fine-granular scalability (FGS) has been accepted as the streaming profile of MPEG-4 to provide a flexible foundation for scaling the enhancement layer (EL) to accommodate variable network capacity. To support smooth quality reconstruction of different rate constraints during transmission, it's significant to acquire the actual rate-distortion functions (RDF) or curves (RDC) of each frame in MPEG-4 FGS videos. In this paper, firstly, we use zero-mean generalized Gaussian distributions (GGD) to model the distributions of 64 (8*8) different discrete cosine transform (DCT) coefficients of FGS EL in a frame. Secondly, we decompose and analyze the FGS coding system using quantization theory and rate-distortion theory, and then combine the analysis of each component together to form a complete RDF of the EL. Guided by the above analysis, at last, we introduce a simple and effective rate-distortion (R-D) model to approximate the actual RDF of the EL in MPEG-4 FGS videos. Extensive experimental results show our statistical model, composition and approximation of actual RDF are efficient and effective. What's more, our analysis methods are general, and the RDF model can also be used in more widely related R-D areas such as rate control algorithms.