A Fidelity-Assured Rate Distortion Optimization Method for Perceptual-Based Video Coding

Rate-distortion optimization (RDO) is one of the essential method to improve the video coding efficiency. The main target of RDO is to find the optimal tradeoff between the reconstructed video quality and encoding rate. In traditional video coding standards, e.g. the emerging H.266/Versatile Video Coding(VVC), the H.265/High Efficiency Video Coding (HEVC) and H.264/Advanced Video Coding (AVC), sum of squared error (SSE) is used as the distortion criterion because SSE can represent the image fidelity efficiently. Based on the existing research on human visual characteristic, the perceptual visual quality is not consistent with image fidelity. Accordingly, we propose a video coding method to improve the subjective quality while avoiding great fidelity degradation. Experimental results demonstrate that the proposed method is efficient in preserving subjective qualities with only a little fidelity degradation when comparing to existing subjective quality based rate distortion optimization methods.

[1]  Christine Guillemot,et al.  Perceptually-Friendly H.264/AVC Video Coding Based on Foveated Just-Noticeable-Distortion Model , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Karl J. Friston,et al.  A free energy principle for the brain , 2006, Journal of Physiology-Paris.

[3]  Wen Gao,et al.  Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization , 2013, IEEE Transactions on Image Processing.

[4]  King Ngi Ngan,et al.  Free-Energy Principle Inspired Video Quality Metric and Its Use in Video Coding , 2016, IEEE Transactions on Multimedia.

[5]  Mohamed-Chaker Larabi,et al.  Asymmetric Dct-Jnd for Luminance Adaptation Effects: an Application To Perceptual Video Coding in Mv-Hevc , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[6]  Zhou Wang,et al.  SSIM-Based Coarse-Grain Scalable Video Coding , 2015, IEEE Transactions on Broadcasting.

[7]  F. Bossen,et al.  Common test conditions and software reference configurations , 2010 .

[8]  Victor Sanchez,et al.  JND-Based Perceptual Video Coding for 4:4:4 Screen Content Data in HEVC , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[9]  Gary J. Sullivan,et al.  Rate-constrained coder control and comparison of video coding standards , 2003, IEEE Trans. Circuits Syst. Video Technol..

[10]  Guangming Shi,et al.  Just Noticeable Difference Estimation for Images With Free-Energy Principle , 2013, IEEE Transactions on Multimedia.

[11]  Gary J. Sullivan,et al.  Rate-distortion optimization for video compression , 1998, IEEE Signal Process. Mag..

[12]  Alan Conrad Bovik,et al.  Large-Scale Study of Perceptual Video Quality , 2018, IEEE Transactions on Image Processing.

[13]  Weisi Lin,et al.  A Psychovisual Quality Metric in Free-Energy Principle , 2012, IEEE Transactions on Image Processing.

[14]  Bin Xu,et al.  CNN-based rate-distortion modeling for H.265/HEVC , 2017, 2017 IEEE Visual Communications and Image Processing (VCIP).

[15]  Nam Ling,et al.  H.264/Advanced Video Control Perceptual Optimization Coding Based on JND-Directed Coefficient Suppression , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[16]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[17]  Guangming Shi,et al.  Survey of visual just noticeable difference estimation , 2019, Frontiers of Computer Science.

[18]  Weisi Lin,et al.  Perceptual visual quality metrics: A survey , 2011, J. Vis. Commun. Image Represent..