Analytical Complexity Modeling of Wavelet-based Video Coders

Analytical modeling for video coders can be used in a variety of scenarios where information concerning rate, distortion or complexity is essential for driving system or network interactions with media algorithms. While rate and distortion modeling have been covered extensively in previous works, complexity is not well addressed because it is highly algorithm dependent and hence difficult to model. Based on a stochastic modeling framework for the transform coefficients, we present a novel complexity analysis for state-of-the-art wavelet video coding methods by explicitly modeling several aspects found in operational coders, i.e. embedded quantization and quadtree decompositions of block significance maps. The proposed modeling derives for the first time analytical estimates of the expected number of operations (complexity) for a broad class of wavelet video coders based on stochastic source models, coding algorithm and system parameters.