Implicit Bit Allocation for Combined Coarse Granular Scalability and Spatial Scalability

Zhengguo Li, Susanto Rahardja, Hanwu Sun

Abstract: A new type of implicit bit allocation (IBA) is studied for the combined coarse granular scalability (CGS) and spatial scalability. Given a region which is a quality level at a spatial resolution and an input of weighting factor in the region that is determined by customers' interest, the IBA is formulated as a multiple objective optimization problem. The IBA exhibits a distinguished feature that allows bits allocation to each region being fixed and only tradeoff between motion information and residual information in each region can be properly set such that coding efficiency of each region is guaranteed in order according to the weighting factor. Due to the nonlinearity of the combined CGS and spatial scalability, this optimization problem is very complex. In this paper, a simple solution to the optimization problem is proposed by using the conventional approach of "Divide and Conquer" or "Hierarchy." Two cross-layer motion estimation/motion compensation (ME/MC) schemes that were introduced for the CGS and spatial scalability are further adopted to support the solution. It is shown that a combined CGS and spatial scalability scheme together with adaptability to customer composition allows the solution to achieve a customer oriented scalable tradeoff (COST)