Convolutional Neural Network Based Fast Intra Mode Prediction for H.266/FVC Video Coding

The next-generation video compression standard H.266/Future Video Coding (FVC) provides high compression efficiency in terms of the cost of computing the optimal intra mode from 67 modes. We propose an intra mode prediction method based on a convolutional neural network (CNN). An input image set of 20 × 20 blocks is used to train the CNN; the CNN is used to predict the best classes of intra mode direction. The CNN architecture comprises two convolutional layers and a fully connected layer. Compared with the default fast search method in FVC, the proposed method can achieve a 0.033% decrease in Bjøntegaard delta bit rate (BDBR) with only a slight increase in time.