Control of video processing algorithms based on measured perceptual quality characteristics

Most consumer electronic devices include a suite of video post-processing algorithms that process the output of the video decoder to drive the video display. In this paper, we propose the use of non-reference video quality metrics to improve the Quality of Experience (QoE) of the user on-the-fly by controlling the parameters of the video post-processing pipeline. We utilize non-reference and real-time measurements of perceptual contrast, sharpness and noise to control denoising and contrast enhancement algorithms in the video post-processing pipeline. We propose methods to ensure consistency of the post-processing across the different frames of the video to avoid creation of flickering artifacts due to variable post-processing. We show that video quality can be improved by identifying the specific quality characteristics that are altered by a video post-processing method and using measurements of these characteristics to improve overall user QoE.