Optimised Compression Strategy in Wavelet-Based Video Coding using Improved Context Models

Accurate probability estimation is a key to efficient compression in entropy coding phase of state-of-the-art video coding systems. Probability estimation can be enhanced if contexts in which symbols occur are used during the probability estimation phase. However, these contexts have to be carefully designed in order to avoid negative effects. Methods that use tree structures to model contexts of various syntax elements have been proven efficient in image and video coding. In this paper we use such structure to build optimised contexts for application in scalable wavelet-based video coding. With the proposed approach context are designed separately for intra-coded frames and motion-compensated frames considering varying statistics across different spatio-temporal subbands. Moreover, contexts are separately designed for different bit-planes. Comparison with compression using fixed contexts from embedded ZeroBlock coding (EZBC) has been performed showing improvements when context modelling on tree structures is applied.