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This paper introduces a novel method for deriving visual saliency maps in real-time without compromising the quality of the output. This is achieved by replacing the computationally expensive centre-surround filters with a simpler mathematical model named Division of Gaussians (DIVoG). The results are compared to five other approaches, demonstrating at least six times faster execution than the current state-of-the-art whilst maintaining high detection accuracy. Given the multitude of computer vision applications that make use of visual saliency algorithms such a reduction in computational complexity is essential for improving their real-time performance.