Optimal quality adaptation for scalable encoded video

The dynamic behavior of the Internet's transmission resources makes it difficult to provide perceptually good quality streaming video. Scalable video encoding techniques have been proposed to deal with this problem. However, an encoded video generally exhibits significant data rate variability to provide consistent visual quality. We are, therefore, faced with the problem of accommodating the mismatch between the available bandwidth variability and the encoded video variability. We investigate quality adaptation algorithms for scalable encoded variable bit-rate video over the Internet. Our goal is to develop a quality adaptation scheme that maximizes perceptual video quality by minimizing quality variation, while at the same time increasing the usage of available bandwidth. We propose an optimal adaptation algorithm and a real-time adaptation algorithm based on whether the network conditions are known a priori. Experimental results show that the real-time adaptation as well as the optimal adaptation algorithm provide consistent video quality when used over both TCP-friendly rate control (TFRC) and transmission control protocol (TCP).