Name
Abstract | ||
|---|---|---|
Down/up-sampling-based video coding is an effective strategy to cope with limited bandwidth for transmission. In recent years, CNN-based super-resolution methods have also been integrated into the above coding strategy. However, it raises a problem of how to balance the calculation and reconstruction quality. In order to alleviate this problem, we propose an enhanced down/up-sampling-based video coding scheme, in which residual data is used to compensate the unrecovered details of the reconstructed video. We first down-sample the video prior to encoding at the encoder and then obtain the residual data by subtracting the super-resolution reconstructed video frame from the original video frame. The residual data is encoded and transmitted together with the low-resolution video sequence. The decoder first reconstructs the encoded low-resolution video with CNN-based super resolution method, and then uses residual data to compensate the missing details of the reconstructed video. To further enhance the perceived quality, we use a quality enhancement network to enhance the quality-compensated video. The experimental results show that the proposed scheme achieves superior quality improvement compared with HEVC anchor and the general down/up-sampling schemes. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICCCS49078.2020.9118561 | 2020 5th International Conference on Computer and Communication Systems (ICCCS) |
Keywords | DocType | ISBN |
video coding,down/up-sampling,residual signal,compensation,Convolutional Neural Network (CNN) | Conference | 978-1-7281-6137-2 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hang Cao | 1 | 0 | 0.34 |
| Xiaowen Liu | 2 | 0 | 0.34 |
| Yida Wang | 3 | 10 | 5.40 |
| Yuting Li | 4 | 0 | 0.34 |
| Weimin Lei | 5 | 29 | 16.35 |