A simple and efficient reduced-reference video quality assessment method based on the activity-difference of DCT coefficients is proposed. The method provides better accuracy, monotonicity, and consistent predictions than the PSNR full-reference metric and comparable results with the full-reference SSIM. It also shows an improved performance to a similar VQ technique based on the calculation of the pixel luminance differences performed in the spatial-domain.

Digital video signals are subject to several distortions due to compression processes, transmission over noisy channels or video processing. Therefore, the video quality evaluation has become a necessity for broadcasters and content providers interested in offering a high video quality to the customers. Thus, an objective no-reference video quality assessment metric is proposed based on the sigmoid model using spatial-temporal features weighted by parameters obtained through the solution of a nonlinear least squares problem using the Levenberg-Marquardt algorithm. Experimental results show that when it is applied to MPEG-2 streams our method presents better linearity than full-reference metrics, and its performance is close to that achieved with full-reference metrics for H.264 streams.