Improved update steps through motion vector correlation analysis for scalable video coding
Recent breakthroughs in motion-compensated temporal filtering (MCTF) has enabled the realization of scalable video coding (SVC). In this paper, we propose a new scheme to improve the update steps of MCTF by analyzing the correlation of the motion vectors (MVs) of the neighboring blocks as well as the correlation of the derived update MVs in the low-pass frames. Results show that the proposed algorithm improves the visual quality of reconstructed video sequences at different bit rates.