Rate and distortion modeling of medium grain scalable video coding
Scalability in video coding is becoming the primary choice for providing quality of service (QoS) guarantees in wireless video communication. In this paper, we develop real-time rate and distortion prediction models for medium grained scalable (MGS) coded video streams. These models allow mobile video encoders to predict the packet size and corresponding distortion of a video frame using only the mean absolute difference (MAD) of the motion prediction and the quantization parameter (QP). The prediction of rate and distortion measures can be used in devices with cross layer optimization capabilities to choose the combination of base and enhancement layer packets that deliver the best picture quality given channel quality information. Performance evaluations demonstrate that our models accurately predict the size and distortion of base and enhancement layer MGS packets.