LAUSR

Scalable video coding (SVC) is a coding paradigm that allows once-encoded video content to be used in diverse scenarios. SVC-coded videos can be transmitted and rendered at specified bitrates according to network bandwidth and end device requirements. In this paper, an adaptive bit allocation algorithm is proposed for the emerging scalable High Efficiency Video Coding (SHVC) standard. The bit budget at the group-of-pictures level is allocated according to buffer occupancy. Picture complexity, measured using the predicted mean absolute difference (MAD), buffer occupancy, and hierarchical level, is proposed for regulating the bitrate at the picture level. The MAD of the current picture is predicted using a novel mean prediction error (MPE) model, which is obtained from the advanced motion vector prediction, and the test zone search specified in SHVC and the associated reference software of SHVC. Moreover, MPE is used to determine the number of assigned bits at the coding-tree-unit level. The bit budget of each level is incorporated with the $R-\lambda $ model for computing the required quantization parameter. Experimental results reveal that the proposed method achieves accurate bitrates with enhanced and consistent visual quality and more satisfactorily controls buffer occupancy compared with the state-of-the-art approaches reported in the literature.