A visual background extracting (Vibe) algorithm based on multiscale space is proposed to solve the problem that there exist ghosts and dynamic background disturbance in the target detection process for the conventional Vibe algorithms. Before the background model is established, the input video sequence is pyramid transformed to obtain three different resolution images at the top, middle, and bottom layers. Then the Vibe foreground detection is performed at different resolutions, and the detection results are fused to reduce the influence of dynamic background. At the same time, a ghost elimination strategy is proposed which enhances the ghost elimination by using the information between frames and by adding a second judgement. Finally, in order to well adapt to the dynamic environment, a metrology under a complex background is proposed, in which the threshold can be adaptively adjusted according to the complexity of backgrounds. The experimental results show that the improved algorithm accelerates ghost elimination and has strong robustness to dynamic environmental noise disturbances.