Scalable motion vector coding

Modern video coding applications require transmission of video data over variable-bandwidth channels to a variety of terminals with different screen resolutions and available computational power. Scalable video coding is needed to optimally support these applications. Recently proposed wavelet-based video codecs employing spatial domain motion compensated temporal filtering (SDMCTF) provide quality, resolution and frame-rate scalability while delivering compression performance comparable to that of the state-of-the-art non-scalable H.264-codec. These codecs require scalable coding of the motion vectors in order to support a large range of bit-rates with optimal compression efficiency. Scalable motion vector coding algorithms based on the integer wavelet transform followed by embedded coding of the wavelet coefficients were recently proposed. In this paper, a new and fundamentally different scalable motion vector codec (MVC) using median-based motion vector prediction is proposed. Extensive experimental results demonstrate that the proposed MVC systematically outperforms the wavelet-based state-of-the-art solutions. To be able to take advantage of the proposed scalable MVC, a rate allocation mechanism capable of optimally dividing the available rate among texture and motion information is required. Two rate allocation strategies are proposed and compared. The proposed MVC and rate allocation schemes are incorporated into an SDMCTF-based video codec and the benefits of scalable motion vector coding are experimentally demonstrated.