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Motion blur compensation in scalable HEVC hybrid video coding

One main element of modern hybrid video coders consists of motion compensated prediction. It employs spatial or temporal neighborhood to predict the current sample or block of samples, respectively. The quality of motion compensated prediction largely depends on the similarity of the reference picture block used for prediction and the current picture block. In case of varying blur in the scene, e.g. caused by accelerated motion between the camera and objects in the focal plane, the picture prediction is degraded. Since motion blur is a common characteristic in several application scenarios like action and sport movies we suggest the in-loop compensation of motion blur in hybrid video coding. Former approaches applied motion blur compensation in single layer coding with the drawback of needing additional signaling. In contrast to that we employ a scalable video coding framework. Thus, we can derive strength as well as the direction of motion of any block for the high quality enhancement layer by base-layer information. Hence, there is no additional signaling necessary neither for predefined filters nor for current filter coefficients. We implemented our approach in a scalable extension of the High Efficiency Video Coding (HEVC) reference software HM 8.1 and are able to provide up to 1% BD-Rate gain in the enhancement layer compared to the reference at the same PSNR-quality for JCT-VC test sequences and up to 2.5% for self-recorded sequences containing lots of varying motion blur.