No-reference video quality metrics are becoming ever more popular, as they
are more useful in real-life applications compared to full-reference
metrics. Many proposed metrics extract features related to human perception
from the individual video frames. Hence the video sequences have to be
decoded first, before the metrics can be applied. In order to avoid the
decoding just for quality estimation, we therefore present in this
contribution a no-reference metric for HDTV that uses features directly
extracted from the H.264/AVC bitstream. We combine these features with the
results from subjective tests using a data analysis approach with partial
least squares regression to gain a prediction model for the visual quality.
For verification, we performed a cross validation. Our results show that
the proposed no-reference metric outperforms other metrics and delivers a
correlation between the quality prediction and the actual quality of 0.93.
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No-reference video quality metrics are becoming ever more popular, as they
are more useful in real-life applications compared to full-reference
metrics. Many proposed metrics extract features related to human perception
from the individual video frames. Hence the video sequences have to be
decoded first, before the metrics can be applied. In order to avoid the
decoding just for quality estimation, we therefore present in this
contribution a no-reference metric for HDTV that uses features d...
»