UC Irvine

Full-reference (FR) video quality estimators (QEs) resize either the distorted input video or the reference video to compute the quality when these videos have different spatial resolutions. This resizing operation causes several limitations. Multiscale Image Quality Estimator (MIQE) overcomes those limitations for images, but it does not consider the temporal characteristics of video. In this paper, we develop an FR video QE that integrates MIQE with the motion information to estimate the quality of the distorted video without resampling the reference or the test videos. We also perform subjective tests to compare the proposed algorithm with the existing QEs. In these tests, the reference and the input videos are displayed at their native resolutions. The test results show that the proposed algorithm outperforms other QEs when the reference video and the input video have different spatial resolutions. We have also evaluated the performance of the approach using the Scalable Video Database.