Modeling Quantization of Affine Motion Vector Coefficients

Affine motion compensated prediction (AMCP) is an advanced tool which may be incorporated into future video compression standards. There are numerous coders already using AMCP [1]–[9]. However the increased number of motion vector components is a disadvantage and quantizing these components can have significant consequences on the difference macro blocks (DMBs). This paper examines the quantization of affine motion vector (AMV) coefficients, by deriving a quadratic relationship between DMB energy and AMV quantization step size. Mathematical derivations and simulations are provided, including two literature comparisons demonstrating the benefits of this work. In the first comparison, the quantization of orthogonalized AMVs in [7] is compared with quantization guided by the novel quadratic model. In the second comparison, Nokia's MVC coder [9] is modified to use the quadratic model to generate quantization step sizes for various granularities; sequence, frame, and quarter-frame, demonstrating up to 8.7% bit rate reductions. Model driven AMV quantization step size choices are shown to be very close to and even outperform limited exhaustive search AMV quantization step size choices, at a quarter of the computational cost.