The invention discloses a time and space significance visual attention method based on entropy, which comprises the following steps that: (1) a dynamic significance figure and a static significance figure in short video are extracted; (2) the static significance figure and the dynamic significance figure are connected to generate a final significance figure; (3) all winners win; (4) return inhibition: the pixel values of the most significant area in the final significance figure are set to be zero to obtain a novel final significance figure; and (5) attention selection. When calculating dynamic significance, the method directly calculates the dynamic significance among all frames and only calculates the static significance figure of a current frame, thereby well solving the problems of the prior art, saving the calculation time and well detecting the dynamic significance part; and in addition, the invention also applies a multi-scale method to calculate the dynamic significance so as to better calculate the dynamic significance of objects with different sizes in the video and obtain good visual effect.