Self learning video filters for wavelet coded video streams

Mobile multimedia systems have to provide mechanisms to cope with the heterogeneity caused by different access network and end system capabilities inherent to wireless communication. Adapting video streams on the fly can be used to match receivers processing and hardware capabilities and the QoS characteristics of wired and wireless links. Within this paper we present a whole suit of filter services that can be applied in order to match frame rate, frame size, visual quality and bandwidth constraints. The filter operate on wavelet coded video streams and adapts them in real-time. A special self learning video filter estimates the source bandwidth of the stream, and times its internal filter operations based on users preferences in order to match a given target bandwidth. We also derive algorithms that map between the filter parameters (i.e. what operations the filters perform) and the resulting bandwidth of the stream