To separate the source image one by one,we consider the blind image extraction of instantaneous mixtures using second-order statistics.A new cost function was constructed first by exploiting the non-stationary properties of image signals,and then the optimal extracted vectors were determined through minimizing the cost function,so as to separate the source image one by one.The simulation results show that the method can achieve the blind separation for mixed images.Moreover,it can separate images with sub-Gaussian distribution and speeches with super-Gaussian distribution.Compared with other conventional algorithms,it has higher accuracy.