A novel GAN-Based Intra Prediction Mode for HEVC
Takafumi Katayama, Tian Song, Takashi Shimamoto, Xiantao Jiang · 2023
Rapid development of AI-IoT environment has great potential for the improvement of video codec technology. The traditional intra prediction in high efficiency video coding (HEVC) generates linear predictions based on some predefined directions for the encoding. However, in the traditional intra prediction method, complex textures need to be encoded by small blocks even if a high resolution video is encoded. To solve this problem, we proposed a new intra prediction mode using the generative adversarial network (GAN). The proposed new framework consists of a traditional video encoder and an embedded generator module including a CNN function. The simulation results show that the proposed algorithm can achieve an improvement of 5.0% BD-rate comparing to the original HEVC algorithm.