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A novel no-reference blockiness metric that can automatically and perceptually quantify blocking artifacts of DCT coding is presented. The proposed metric is built upon the specific structure information of the artifact itself combined with the properties of the human visual system (HVS) by means of a simple and efficient model of visual masking. Investigations are conducted to reduce the additional cost introduced by the human vision model, without compromising its overall prediction ability. The proposed metric is validated through comparing its performance to state-of-the-art HVS model based blockiness metrics with respect to accuracy, reliability and computational complexity.