Flicker sensitive motion tuned video quality assessment
Lark Kwon Choi, Alan Conrad Bovik · 2016
From a series of human subjective studies, we have found that large motion can strongly suppress flicker visibility. Based on the spectral analysis of flicker videos in frequency domain, we propose a full reference video quality assessment (VQA) framework that incorporates flicker sensitive temporal visual masking. The framework predicts perceptually silenced flicker visibility using a model of the responses of primary visual cortex to video flicker, a motion energy model, and divisive normalization. By incorporating perceptual flicker visibility into motion tuned video quality measurements as in the MOVIE framework, we augment VQA performance with sensitivity to flicker. Results show that the proposed VQA framework correlates well with human results and is highly competitive with recent state-of-the-art VQA algorithms tested on the LIVE VQA database.