Multi-Stage MCTF Coding Efficiency Analysis with Directed-Tree Model
Motion-compensated temporal filtering (MCTF) was believed to improve coding efficiency due to its temporal noise filtering capability. However, recent experimental results in scalable video coding (SVC) development revealed that MCTF update steps at the decoder side do not always contribute significantly to the coding efficiency. In this paper, we present a novel directed-tree model to analyze the lifting-based multi-decomposition stage MCTF coding efficiency. It shows that with skipping the inverse update steps at the decoder side, MCTF performance converges against an upper bound, which depends on the actual prediction and the adaptive weighting algorithms. The results in our study provide a theoretical justification for not including MCTF update steps in the decoding process for scalable video coding