Perceptual coding scheme for ultra-high definition video based on perceptual noise channel model

Abstract Perceptual video coding (PVC) can eliminate visual redundancy and effectively improve the compression performance of ultra-high definition video. The conventional PVC schemes, involving the perceptual characteristics related to the video features, do not account for interference in the human visual system caused by external environment changes. Therefore, this paper presents a PVC scheme based on a perceptual noise channel model. In this approach, visual dither is utilized to imitate the adjustment process of human eyes while environment changes. Considering reliable external visual stimulus decoding in the perceptual noise channel and visual characteristics, dynamic estimation of visual dither quantization is performed based on a message passing algorithm on a factor graph. Furthermore, a weight factor based on the perceptual noise channel capacity is incorporated into the rate distortion optimization process. The experimental results show that the proposed PVC scheme achieves significant bitrate reduction with better subjective video quality than competitive PVC schemes.