Encoding stored video for streaming applications

In streaming video applications, video sequences are encoded off-line and stored in a server. Users may access the server over a constant bit rate channel. Examples of the streaming video applications are video-on-demand, archived video news, and noninteractive distance learning. Before the playback, part of the video bitstream is pre-loaded in the decoder buffer to ensure that every frame can be decoded at the scheduled time. For these streaming video applications, since the video is encoded off-line and the future video frames are available to the encoder, a more sophisticated bit-allocation scheme can be used to achieve better video quality. During the encoding process for streaming video, two requirements need to be considered: the pre-loading time that the video viewers have to wait and the physical buffer-size at the receiver (decoder) side. In this paper, we propose a sliding-window rate-control scheme that uses statistical information of the future video frames as a guidance to generate better video quality for video streaming involving constant bit rate channels. A quantized discrete cosine transform coefficient selection scheme based on the rate-distortion measurement is also used to improve the video quality. Simulation results show video quality improvements over the regular H.263 TMN8 encoder