A metric for continuous quality evaluation of compressed video with severe distortions

Abstract An objective quality metric that generates continuous estimates of perceived quality for low bit rate video is introduced. The metric is based on a multichannel model of the human visual system. The vision model is initially parameterized to threshold data and then further optimized using video frames containing severe distortions. The proposed metric also discards processing of the finest scales to reduce computational complexity, which also results in an improvement in the accuracy of prediction for the sequences under consideration. A temporal pooling method suited to modeling continuous time waveforms is also introduced. The metric is parameterized and evaluated using the results of a Single Stimulus Continuous Quality Evaluation test conducted for CIF video at rates from 100 to 800 kbps . The proposed metric exceeds the performance of a similar metric based on the Mean Squared Error.

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