Generic modeling of complexity for motion-compensated wavelet video decoders

Motion-compensated wavelet video coders have been shown to exhibit good coding efficiency over a large range of bit-rates, in addition to providing spatial and temporal scalability. While the rate-distortion performance provided by these coders is well understood, their complexity scalability behavior is not well studied. In this paper, we first analyze the complexity of such wavelet video coders, and determine what the critical components are and how they vary depending on the transmission bit-rates. Subsequently, we construct generic complexity models for the critical components of the scalable wavelet video decoders; such that optimal rate, distortion and complexity bitstreams can be created that fulfill not only various network constraints, but also resource constraints such as memory and power. The generic complexity metrics are independent of the hardware architecture and implementation details of the decoders and capture both the time varying video content characteristics and the corresponding encoding parameters. The generic complexity measures can be converted into real platform specific complexity measures like execution time with limited overhead at runtime. Preliminary results show that the proposed models can predict the complexity of the various components of wavelet video decoders with high accuracy.