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Visibility prediction of flicker distortions on naturalistic videos

机译:自然视频闪烁变形的可见性预测

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We conducted a series of human subjective studies where we found that the visibility of flicker distortions on naturalistic videos is strongly reduced when the speed of coherent object motion is large. Based on this, we propose a model of flicker visibility on naturalistic videos. The model predicts target-related activation levels in the excitatory layer of neurons for a video using spatiotemporal backward masking. The target-related activation level is then shifted and scaled according to video quality level changes that cause flicker distortions. Finally, flicker visibility is predicted based on neural flicker adaptation processes. Results show that the predicted flicker visibility using the model correlates well with human perception of flicker distortions on naturalistic videos.
机译:我们进行了一系列人类主观研究,发现当相干物体运动的速度较大时,自然视频上的闪烁失真的可见性会大大降低。基于此,我们提出了一种在自然视频上闪烁可见性的模型。该模型使用时空后向掩盖预测视频的神经元兴奋层中与目标相关的激活水平。然后,根据目标质量的激活水平根据会导致闪烁失真的视频质量水平变化进行移动和缩放。最后,基于神经闪烁适应过程来预测闪烁可见性。结果表明,使用该模型预测的闪烁可见性与人类对自然视频上的闪烁失真的感知密切相关。

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