Simplified Inception Unit based Filter for HEVC
Peidi Yi, Shengwei Wang, Hongkui Wang, Li Chen Yu · 2019
The HEVC standard has shown great effect in video coding, however, the block-level compression scheme introduces block artifacts into reconstructed videos. Meanwhile, the quantization also brings ringing effect and blur to the compressed sequence. In order to solve this problem, we propose a simplified inception unit based convolutional neural network to reduce the compression distortion in HEVC. In the proposed method, a simplified inception unit is designed to analyze and extract image features. By stacking multiple inception units, the internal and border information of each frame can be fully extracted and the images are able to achieve higher quality. Meanwhile, the proposed network is incorporated into the HEVC reference software, which can be directly used in coding process and improve coding performance. The experimental results demonstrate that the proposed method, compared with HEVC, reduces 5.5% BDrate at average in `Al' mode. In `RA' mode, the proposed method still achieves 6.02% BD-rate reduction at most.