Arithmetic coding using hierarchical dependency context model for H.264/AVC video coding

In this paper, a hierarchical dependency context model (HDCM) is firstly proposed to exploit the statistical correlations of DCT (Discrete Cosine Transform) coefficients in H.264/AVC video coding standard, in which the number of non-zero coefficients in a DCT block and the scanned position are used to capture the magnitude varying tendency of DCT coefficients. Then a new binary arithmetic coding using hierarchical dependency context model (HDCMBAC) is proposed. HDCMBAC associates HDCM with binary arithmetic coding to code the syntax elements for a DCT block, which consist of the number of non-zero coefficients, significant flag and level information. Experimental results demonstrate that HDCMBAC can achieve similar coding performance as CABAC at low and high QPs (quantization parameter). Meanwhile the context modeling and the arithmetic decoding in HDCMBAC can be carried out in parallel, since the context dependency only exists among different parts of basic syntax elements in HDCM.

[1]  Joseph W. Goodman,et al.  A mathematical analysis of the DCT coefficient distributions for images , 2000, IEEE Trans. Image Process..

[2]  Ian H. Witten,et al.  Arithmetic coding revisited , 1998, TOIS.

[3]  Guillermo Sapiro,et al.  The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS , 2000, IEEE Trans. Image Process..

[4]  Xiaolin Wu,et al.  Lossless compression of continuous-tone images via context selection, quantization, and modeling , 1997, IEEE Trans. Image Process..

[5]  Lu Yu,et al.  Overview of AVS-video coding standards , 2009, Signal Process. Image Commun..

[6]  David S. Taubman,et al.  High performance scalable image compression with EBCOT , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

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

[8]  Anantha Chandrakasan,et al.  Parallel CABAC for low power video coding , 2008, 2008 15th IEEE International Conference on Image Processing.

[9]  Ki-Seok Chung,et al.  Multi-threaded syntax element partitioning for parallel entropy decoding , 2011, IEEE Transactions on Consumer Electronics.

[10]  Heiko Schwarz,et al.  Entropy coding in video compression using probability interval partitioning , 2010, 28th Picture Coding Symposium.

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

[12]  Gwanggil Jeon,et al.  Arithmetic coding for image compression with adaptive weight-context classification , 2013, Signal Process. Image Commun..

[13]  Heiko Schwarz,et al.  Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[14]  JORMA RISSANEN,et al.  A universal data compression system , 1983, IEEE Trans. Inf. Theory.

[15]  Wen Gao,et al.  High Efficient Context-Based Variable Length Coding with Parallel Orientation , 2005, PCM.

[16]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[17]  Jorma Rissanen,et al.  Applications of universal context modeling to lossless compression of gray-scale images , 1995, Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers.

[18]  Madhukar Budagavi,et al.  High Throughput CABAC Entropy Coding in HEVC , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[19]  Francesc Auli-Llinas Entropy-Based Evaluation of Context Models for Wavelet-Transformed Images , 2015, IEEE Transactions on Image Processing.

[20]  Nasir D. Memon,et al.  Context-based, adaptive, lossless image coding , 1997, IEEE Trans. Commun..

[21]  Xiaolin Wu,et al.  Context quantization by kernel Fisher discriminant , 2006, IEEE Transactions on Image Processing.

[22]  Wen Gao,et al.  A parallel context model for level information in CABAC , 2011, 2011 Visual Communications and Image Processing (VCIP).

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

[24]  Wen Gao,et al.  Context-based entropy coding in AVS video coding standard , 2009, Signal Process. Image Commun..

[25]  G. Bjontegaard,et al.  Calculation of Average PSNR Differences between RD-curves , 2001 .

[26]  Shuming Chen,et al.  P3-CABAC: A Nonstandard Tri-Thread Parallel Evolution of CABAC in the Manycore Era , 2010, IEEE Transactions on Circuits and Systems for Video Technology.