A block-adaptive skip mode for inter prediction based on parametric motion models

Motion compensated prediction (MCP) in hybrid video coding estimates a translational motion vector for a given block which is then used for residual computation. However, when complex motion like zoom, rotation, and perspective transformation occur, the translational model assumption does not always hold. This may result in higher residual energy and splitting of blocks, respectively. This paper proposes a skip mode based on higher-order parametric motion models. Often, these models provide a better prediction quality resulting in lower residual energy and larger block sizes. The proposed technique estimates a higher-order motion model between two given pictures. The encoder decides in terms of rate-distortion optimization whether to use the new skip mode for a block and therefore not to transfer any additional information like coefficient data. Experimental evaluation shows that the proposed technique can improve the coding performance of next generation video coding standards significantly.