This paper proposed an objective video quality metric designed for automatically assessing the perceived quality of digitally compressed multimedia videos using H.264 video compression. The rationale in proposing perceptual-based metric is because traditional measure, peak signal-to-noise ratio (PSNR), has been found to correlate poorly with subjective quality ratings, particularly at much lower bit rates. In this paper, computational models have been applied to emulate human visual perception based on a combination of local and global modulating factors. The proposed video quality metric has been tested on CIF and QCIF video sequences compressed using H.264 video compression technique at various bit rates (24-384 Kbps) and frame rates (7.5-30Hz). Performance of the proposed metric with respect to subjective scores will be reported and a comparison with PSNR and also the video structural similarity method (being one of the best video quality metric for high bit rate videos recently reported in the literature) will also be provided in this paper.