Noise variance adaptive successive elimination algorithm for block motion estimation: application for video surveillance
W.-G. Chen, Yun Ling · IET Signal Processing · 2007
In a practical video encoder, a video sequence obtained from a camera inevitably conveys noise. The noise term degrades not only image quality but also coding efficiency. Based on the statistical analysis of noise signal, a two-stage noise variance adaptive successive elimination algorithm (SEA) for block motion estimation is presented. To reduce the additional computation cost required for video noise estimation, it is embedded into the process of block matching using Kalman filtering. Simulation results demonstrate that the performance of the proposed algorithm is close to that of the SEA, whereas the computational complexity has been significantly reduced.