Perceptual Video Quality Assessment Based on Salient Region Detection

Video based applications and services usually require at some stage a reliable video quality evaluation method that can give an estimate for the human perceived video quality. While most research is performed in the area of human visual system modeling, we propose a quality metric which first estimates the perceptually important areas using the key elements that attract the attention: color contrast, object size, orientation and eccentricity. The visual attention model implemented here performs as a bottom-up attentional mechanism. For the salient areas detected, a distortion measure is then computed using a specialized no-reference metric. We propose an embedded reference-free video quality metric and show that it outperforms the standard peak signal to noise ratio in evaluating the perceived video quality. The results are also shown to correlate with the subjective results obtained for several test sequences.