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Considering the spatial and temporal channel of the human visual system both include the second derivative of Gaussian function, we first construct a three-dimensional LOG (3D LOG) filter to simulate human visual filter and to extract the perceptual-aware features for the design of VQA algorithms. Moreover, since the correlation measuring based on 2D LOG filtering of video spatiotemporal slice (STS) images can capture the distortion of spatiotemporal motion structure accurately and effectively, then we apply the 2D LOG filtering to video STS images and using maximum pooling for distortion of vertical and horizontal STS images to improve prediction accuracy.
The performance of proposed algorithms is validated on the LIVE VQA database. The Spearman’s rank correlation coefficients of the proposed algorithms are all above 0.82, which shows that our methods are better than that of most mainstream VQA methods.
Motion artifacts reduction in 4DCBCT based on motion-compensated robust principal component analysis
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