SUMMARYIn this paper, we propose an error resilience scheme for wireless video coding based on adaptive flexible macroblock ordering (FMO) and intra refresh. An FMO explicit map is generated frame-byframe by using prior information. This information involves estimated locations of guard and burst sections in the channel and estimated effect of error propagation (EEP) from the previous frame to the current frame. In addition, the role of the current frame in propagating an error to the next frame is also considered. A suitable intra refresh rate which is adaptive to the channel state is used to reduce the dependence between frames and thus can stop the EEP. The results in experiments show that the proposed method gains some improvements in terms of peak signal-to-noise rate (PSNR) as compared with some other methods that have not considered the channel condition and the error propagation in generating an FMO map. key words: H.264, FMO, error propagation, intra refresh, error resilience
Versatile Video Coding (VVC) has been recently becoming popular in coding videos due to its compression efficiency. To reach this performance, Joint Video Experts Team (JVET) has introduced a number of improvement techniques to VVC coding model. Among them, VVC Intra coding introduces a new concept of quad-tree nested multi-type tree (QTMT) and extends the predicted modes with up to 67 options. As a result, the complexity of the VVC Intra encoding also greatly increases. To make VVC Intra coding more feasible in real-time applications, we propose in this paper a novel deep learning based fast QTMT and an early mode prediction method. At the first stage, we use a learned convolutional neural network (CNN) model to predict the coding unit map and then fed into the VVC encoder to early terminate the block partitioning process. After that, we design a statistical model to predict a list of most probable modes (MPM) for each selected Coding using (CU) size. Finally, we employ a so-called three-steps mode decision algorithm to estimate the optimal directional mode without sacrificing the compression performance. The proposed early CU splitting and fast intra prediction are integrated into the latest VTM reference software. Experimental results show that the proposed method can save 50.2% of encoding time with a negligible BD-Rate increase.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.