CNN Based Optimal Intra Prediction Mode Estimation in Video Coding
Ryota YOKOYAMA, Masahiko Tahara, Masaru Takeuchi, Heming Sun, Yasutaka MATSUO, Jiro Katto · 2020
The amount of video data is so large that efficient video compression is required for the storage and transmission. Intra prediction is one of important components in video compression. In this paper, we examine various Convolutional Neural Network (CNN) structures to estimate optimal intra prediction mode as Most Probable Modes (MPMs). Moreover, we investigate several combinations of the MPMs obtained by the CNN and MPMs derived from High Efficiency Video Coding Test Model (HM). From these experimental results, we find that using 6 MPMs from both CNN and HM with moderate number of channels or kernel size is preferred.