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The study of the human visual system is very interesting to quantify the quality of an image or to predict perceived information. The contrast sensitivity function is one of the main ways to incorporate the human visual system properties in an imaging system. It characterizes its sensitivity to spatial frequencies. In this paper, we are interested in establishing a pretreatment for existing metrics with full reference ("peak signal-to-noise ratio", "digital video quality") for the H.264/MPEG-4 (Motion Picture Expert Group) advanced video coding standard. We realize in our algorithm the FFT transformation to apply the contrast sensitivity function. Our method is applicable to any size of image and video sequence by increasing its size at powers of two. This increase is achieved by adding "mirror image." We evaluate the performance of the proposed pretreatment by using subjective "LIVE" video databases. The performance metrics, that is, Pearson (PLCC), Spearman correlation coefficients (SROCC) and root mean square prediction error (RMSE) indicate that the proposed method gives a good performance in H264 codec distortions.Keywordsvideo quality assessment, "peak signal-to-noise ratio", "digital video quality", "contrast sensitivity function", "human visual system", "fast Fourier transform", zero padding, H.264/ MPEG-4 AVC.

International audienceThe need to measure video quality arises in the development of video equipment and in the delivery and storage of video and image information. In this paper, we propose a new perceptually significant video quality metric to estimate the effect of block coding for standards H.264 AVC and MPEG2. Our method operates in the spatial domain and does not require a high complexity of computation. We evaluate the performance of the proposed method by using three sequences CIF ‘common intermediate file’ with different compression rate. We compare it with Suthaharan’s and MSU’s techniques by using ‘LIVE’ and ‘IVP’ databases. Results indicate that the proposed method outperforms Suthaharan’s and MSU techniques in H264 coder. They also indicate that our method is more effective than MSU’s and Suthaharan’s techniques for the H.264 AVC standards with the Spearman Rank Order Correlation Coefficient

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