Adaptive Multi-Scale Progressive Probability Model For Lossless Image Compression

in the past few years, several efforts have been devoted to reduce individual sources of latency, including acquisition, coding and network transmission, with the goal to improve the quality of experience in applications requiring real-time interaction. However, these efforts are fundamentally constrained by technological and physical limits. in this paper, we investigate a radically different approach that can arbitrarily reduce the overall latency by means of video extrapolation. We propose two latency compensation schemes where video extrapolation is performed either at the encoder or at the decoder side. Since a loss of fidelity is the price to pay for compensating latency arbitrarily, we study the latency-fidelity distortion using three recent video prediction schemes. Our preliminary results show that by accepting a quality loss, we can reduce a typical latency of 100 ms with a loss in excess of 8 dB with our best extrapolator. This suggests that further work should be done in future video prediction to pursue zero-latency video transmission.