Month: October 2018

ViSTRA: Video Compression based on Resolution Adaptation

Posted on by Aaron

Fan Zhang, Mariana Afonso and David Bull

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 Bjonegaard 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.

PROPOSED ALGORITHM

RESULTS

BD-rate results of ViSTRA2 when HM 16.20 was employed as host codec.

BD-rate results of ViSTRA2 when VTM 4.01 was employed as host codec.

REFERENCE

[1] F. Zhang, M. Afonso and D. R. Bull, ViSTRA2: Video Coding using Spatial Resolution and Effective Bit Depth Adaptation. arXiv preprint arXiv:1911.02833.

[2] M. Afonso, F. Zhang and D. R. Bull, Video Compression based on Spatio-Temporal Resolution Adaptation. IEEE T-CSVT (Letter), 2019.

[3] M. Afonso, F. Zhang, A. Katsenou, D. Agrafiotis, D. Bull, Low Complexity Video Coding Based on Spatial Resolution Adaptation, ICIP, 2017.

Rate-distortion Optimization Using Adaptive Lagrange Multipliers

Posted on by Aaron

Fan Zhang and David Bull

ABSTRACT

This page introduces the work of rate-distortion optimisation using adaptive Lagrange Multipliers. In current standardized hybrid video encoders, the Lagrange multiplier determination model is a key component in rate-distortion optimization. This originated some 20 years ago based on an entropy-constrained high-rate approximation and experimental results obtained using an H.263 reference encoder on limited test material. In this work, we conducted a comprehensive analysis of the results of a Lagrange multiplier selection experiment conducted on various video content using H.264/AVC and HEVC reference encoders. These results show that the original Lagrange multiplier selection methods, employed in both video encoders, are able to achieve optimum rate-distortion performance for I and P frames, but fail to perform well for B frames. The relationship is identified between the optimum Lagrange multipliers for B frames and distortion information obtained from the experimental results, leading to a novel Lagrange multiplier determination approach. The proposed method adaptively predicts the optimum Lagrange multiplier for B frames based on the distortion statistics of recent reconstructed frames. After integration into both H.264/AVC and HEVC reference encoders, this approach was evaluated on 36 test sequences with various resolutions and differing content types. The results show consistent bitrate savings for various hierarchical B frame configurations with minimal additional complexity. BD savings average approximately 3% when constant QP values are used for all frames, and 0.5\% when non-zero QP offset values are employed for different B frame hierarchical levels.

 

REFERENCE

[1] Fan Zhang and David, R. Bull, “Rate-distortion Optimization Using Adaptive Lagrange Multipliers”, IEEE Trans. on CSVT, accepted in 2018.

[2] F. Zhang and D. Bull, “An Adaptive Lagrange Multiplier Determination Method for Rate-distortion Optimisation in Hybrid Video Codecs”. IEEE ICIP, 2015.