In this paper, a novel saliency map generation approach based on the saccade target theory is proposed. A probabilistic model of transsaccadic integration is built based on four cues that influence human visual attention: foveaperiphery resolution discrepancy, visual memory, oculomotor bias and inhibition of return (IOR), where visual memory is formulated as combination of the visual short-term memory (VSTM) and the visual long-term memory (VLTM). A sequence of fixations is generated based on the model to simulate the shift of attention. The proposed approach is evaluated on both perspectives of the accuracy of generated saliency maps and scanpaths. As demonstrated in the experiments, our method provides better estimated saliency maps and scanpaths on eye tracking datasets when compared to several state-of-the-art models.