Rate model considering inter-symbol dependency for HEVC inter-frame coding

In this paper, an accurate rate model is proposed for inter-frame coding of high-efficiency video coding, which is useful for rate control. The proposed model considers the effect of entropy coding where the inter-symbol dependency is exploited in context- adaptive binary arithmetic coding (CABAC) for saving coded bits. The mutual information is first predicted to measure the reduction of uncertain information in CABAC, and then the conditional entropy is calculated to estimate the output bit-rate of inter-frame residues. Since the source characteristic also significantly impacts on the building of rate model, a joint Laplacian distribution source at the transform unit levels is employed in the proposed rate model. The experimental results show that the proposed model achieves a better rate-distortion performance in rate control. The proposed approach can be also extended to other video codecs using CABAC for the design of rate models.

[1]  King Ngi Ngan,et al.  Recent advances in rate control for video coding , 2007, Signal Process. Image Commun..

[2]  Wen Gao,et al.  Rate-GOP Based Rate Control for High Efficiency Video Coding , 2013, IEEE Journal of Selected Topics in Signal Processing.

[3]  Gary J. Sullivan,et al.  Overview of the High Efficiency Video Coding (HEVC) Standard , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[4]  Munchurl Kim,et al.  Modeling Rates and Distortions Based on a Mixture of Laplacian Distributions for Inter-Predicted Residues in Quadtree Coding of HEVC , 2011, IEEE Signal Processing Letters.

[5]  Marta Karczewicz,et al.  Transform Coefficient Coding in HEVC , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  Tihao Chiang,et al.  A new rate control scheme using quadratic rate distortion model , 1997, IEEE Trans. Circuits Syst. Video Technol..

[7]  Truong Q. Nguyen,et al.  A Frame-Level Rate Control Scheme Based on Texture and Nontexture Rate Models for High Efficiency Video Coding , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[8]  Gary J. Sullivan,et al.  Comparison of the Coding Efficiency of Video Coding Standards—Including High Efficiency Video Coding (HEVC) , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[9]  S. Liu,et al.  Statistical analysis of the DCT coefficients and their quantization error , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[10]  David R. Brillinger,et al.  Some data analyses using mutual information , 2004 .

[11]  Nouri Masmoudi,et al.  Fast coding unit partitioning method based on edge detection for HEVC intra-coding , 2016, Signal Image Video Process..

[12]  Houqiang Li,et al.  $\lambda $ Domain Rate Control Algorithm for High Efficiency Video Coding , 2014, IEEE Transactions on Image Processing.

[13]  Gary J. Sullivan,et al.  High Efficiency Video Coding (HEVC), Algorithms and Architectures , 2014, Integrated Circuits and Systems.

[14]  Pierre Moulin,et al.  Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients , 2001, IEEE Trans. Image Process..

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

[16]  Trac D. Tran,et al.  Context-based entropy coding of block transform coefficients for image compression , 2002, IEEE Trans. Image Process..

[17]  Tao Zhu,et al.  Research on statistical distributions of transform coefficients for H.264/SVC , 2010, 2010 3rd International Congress on Image and Signal Processing.

[18]  Yo-Sung Ho,et al.  Efficient residual data coding in CABAC for HEVC lossless video compression , 2015, Signal Image Video Process..

[19]  Yücel Altunbasak,et al.  An analysis of the DCT coefficient distribution with the H.264 video coder , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.