ViSTRA2: Video Coding using Spatial Resolution and Effective Bit Depth Adaptation
arXiv:1911.02833 · doi:10.1016/j.image.2021.116355
Abstract
We present a new video compression framework (ViSTRA2) which exploits adaptation of spatial resolution and effective bit depth, down-sampling these parameters at the encoder based on perceptual criteria, and up-sampling at the decoder using a deep convolution neural network. ViSTRA2 has been integrated with the reference software of both the HEVC (HM 16.20) and VVC (VTM 4.01), and evaluated under the Joint Video Exploration Team Common Test Conditions using the Random Access configuration. Our results show consistent and significant compression gains against HM and VVC based on Bjønegaard Delta measurements, with average BD-rate savings of 12.6% (PSNR) and 19.5% (VMAF) over HM and 5.5% (PSNR) and 8.6% (VMAF) over VTM.
9 pages
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Cited by in corpus (12)
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- RMT-BVQA: Recurrent Memory Transformer-based Blind Video Quality Assessment for Enhanced Video Content
- CAESR: Conditional Autoencoder and Super-Resolution for Learned Spatial Scalability
- ViSTRA3: Video Coding with Deep Parameter Adaptation and Post Processing
- Enhancing HDR Video Compression through CNN-based Effective Bit Depth Adaptation