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A common framework for rate and distortion based scaling of highly scalable compressed video

Scalability refers to the ability to modify the resolution and/or bit rate associated with an already compressed data source in order to satisfy requirements which could not be foreseen at the time of compression. A number of researchers have already demonstrated the feasibility of efficient scalable image and video compression. The principle focus of this paper is to describe data structures for highly scalable compressed video, which are able to support simple, generic scaling approaches for both constant bit rate and constant distortion scaling criteria. Interactive video material presents particular challenges when the data stream is to be scaled to maintain an approximately constant level of distortion, rather than just a constant bit rate. Special attention is paid, therefore, to the development of generic, robust scaling algorithms for such applications. The data structures and scaling methodologies developed are particularly appealing for the distribution of highly scalable compressed video over heterogeneous media, because they simultaneously support both variable bit rate (VBR) and constant bit rate (CBR) services with a wide range of available service qualities, using only simple, generic mechanisms for scaling. The performance of the proposed scaling methodologies is experimentally investigated using a highly scalable video compression algorithm, which is able to achieve comparable compression performance to that of the inherently nonscalable MPEG-1 compression standard.