关键词: 运动估计, 卡尔曼滤波, 中值滤波, 视频去噪

Abstract: There is an irreconcilable conflict between the degree of vagueness and the capacity of denoising in conventional image filters.A new video based denoising method，combining special and temporal filters，utilizing both spatial correlation and temporal correlation，is proposed to solve this problem.At first the motion trajectory is gained by a fast adaptive motion estimation method with adaptive thresholds and different search modes.Then a window-size adaptive median filtering is performed with the two windows on the motion trajectory of current and last frame.The temporal redundancy is exploited by a scalar state 1-D Kalman filter.A novel way is proposed to estimate the variance of the state noise from the noisy frames.At last the two estimates are combined with a geometric mean take full advantage of both spatial and temporal relativities.Experimental result shows that the new method is robust than both spatial and temporal methods，especially when treating the pepper & salt noises.As the time consumption of the new method is sum of temporal filter，spatial filter and motion estimation，the computational complexity increased by combination is acceptable，which is also proved in experiments.

Key words: motion estimation, Kalman filtering, median filtering, video denoising