Review: S-CNN & C-CNN — Adaptively Iterative In-loop Filter in HEVC (Codec Filtering)

Original article can be found here (source): Deep Learning on Medium

Review: S-CNN & C-CNN — Adaptively Iterative In-loop Filter in HEVC (Codec Filtering)

SRCNN-like Network, With Residual Learning Intorduced by ResNet, Up to 5.1% Bitrate Reduction is Obtained

In this story, Simplfied CNN (S-CNN) & Complicated CNN (C-CNN), by National Taiwan Normal University, National Sun Yat-sen University, National Dong Hwa University and Yuan Ze University, is reviewed.

The Proposed CNN Enhancement Mode is the In-loop Filter

In-loop filter is used to enhance the video frame quality before the video frame is used for viewing or prediction. With higher quality, better prediction can be obtained for the next frame. Bitrate can also be reduced due to the better prediction. (To know more about in-loop filter, please read DRN.)

  • For S-CNN, an early termination mechanism is proposed to further reduce the HEVC encoding complexity.
  • With regard to C-CNN, a GPU-based heterogeneous architecture is proposed to accelerate CNN processing.

This is a paper in 2018 ACCESS. This is an open-access journal with high impact factor of 4.098. All papers can be downloaded free of charge even for non IEEE members. (Sik-Ho Tsang @ Medium)