Distance scaling of higher order motion parameters in an extension of HEVC
Cordula Heithausen, Max Bläser, Mathias Wien · 2016
Complex motion in video sequences, such as rotation and scaling, conventionally approximated translationally, can more efficiently be represented by higher order motion models. An important contribution to the efficiency of the higher order motion compensation approach is the prediction and encoding of the additional motion parameters. The additional data rate caused by an increased amount of motion parameters has to be kept small for the higher order motion model to outperform the translational one within blocks of complex motion. Addressing an aspects of motion prediction yet to be adjusted to higher order motion, this paper proposes an advanced method of distance scaling of higher order motion parameters. Just as translational motion vector predictors require scaling whenever the block inheriting them has a different distance to its reference picture than the block predicted from, higher order motion parameter prediction can profit from such scaling as well. However, the distance scaling of higher order motion parameters cannot be applied to the elements of the motion model transformation matrix directly, but is performed on separate higher order motion components provided by a preceding transformation matrix decomposition. Accordingly, the objective of this work is to introduce and evaluate a procedure for higher order motion distance scaling. The resulting rate reduction of about 2% on average and up to over 6% attains a further improvement on the higher order motion compensation in an extension of HEVC.