Resolution-scalable coding of video using motion-compensated temporal filtering and multistage quantization

The scalable transmission of video data has become increasingly important as network technologies advance. Today it is common for networks to consist of a diverse spectrum of clients with widely varying display and processing capabilities. In such a heterogeneous environment, it is important that each client be efficiently serviced according to the client's capabilities. Scalable data streams are an ideal solution since each client can selectively receive or route to a lower bandwidth subnet the maximum amount of manageable data from one broadcast stream. This technology has applications in such areas as network simulcasts, video conferencing, multimedia, database browsing, and standards compatibility.;A new source coding algorithm is proposed which delivers an encoded bit stream that is scalable in both spatial resolution and frame rate. Motion compensated temporal filtering is combined with a spatial subband pyramid to provide an efficient 3-D multiresolution representation that yields perceptually acceptable low frame rate sequences. Error feedback hierarchical coding is used to eliminate the propagation of coding errors between spatiotemporal resolutions in order to achieve jointly optimal results for each subvideo. The proposed ordering of refinement addresses the non-commutative property of motion compensated temporal filtering and spatial subband analysis. A new algorithm based on adaptive conditional arithmetic coding of quantizer significance maps is introduced and is shown to increase coding efficiency.;Experimental results demonstrate a significant improvement in performance over other published algorithms. The algorithm is found to be more robust with respect to variations in the type of motion present in video data. The code-and-refine nature of the hierarchical algorithm makes it possible to use the algorithm as a scalable extension to other source coding algorithms. Finally, the complexity of the algorithm is modest and is well suited to a parallel implementation.