Deep CNN Depth Decision in Intra Prediction

The video and its compression become prominent with the emergence of digital video technology and common use of video acquisition devices. The traditional video compression needs upgradation with artificial intelligence, machine learning, neural network, and deep learning. Apart from normal signal processing the deep learning technologies are advantages as they can deal with content analysis than dealing only with neighboring pixels. The initial steps in video compression, intra/inter frame prediction provide a better percentage in overall compression. The computational complexity of existing intra prediction method is more. This paper proposes a deep learning based intra prediction method using CNN. This deep depth prediction algorithm trains the network to provide depth of the CTU with reduced computation and less time. The experimental results show a dip in the encoding time, about 71.3% compared to existing method.