Abstract
Rate control plays an important role in high efficiency video coding (HEVC), and bit allocation is the foundation of rate control. The video content characteristics are significant for bit allocation, and modeling an accurate relationship between video content characteristics and bit allocation is essential for bit allocation optimization. Therefore, in this article, a video content characteristics–based frame-level optimal bit allocation algorithm is proposed for improving the rate distortion (RD) performance of HEVC. First, the number of search points of motion estimation is used to evaluate the motion activity of video content, and the relationship between the search points and bit allocation is modeled as the search-points model. Second, the grey level co-occurrence matrix and temporal perceptual information are used to evaluate the spatial and temporal texture complexity, and the relationship between the video content texture complexity and bit allocation is modeled as the texture-complexity model. Then, the search-points model and texture-complexity model are jointly employed to allocate the coding bits for the second and third layers of the HEVC hierarchical coding structure. Finally, the remaining coding bits of a group-of-pictures (GOP) are allocated to the first layer of HEVC coding structure. To evaluate the performance of the proposed algorithm, the RD performance and bitrate accuracy are used as evaluation criteria, and the experimental results show that when compared with the popularly used R-λ model–based bit allocation algorithm, the proposed algorithm achieves an average of -3.43% BDBR reduction and 0.13 dB BDPSNR gains with only 0.02% loss of bitrate accuracy.
- Manish H. Bharati, J. Jay Liu, and John F. MacGregor. 2004. Image texture analysis: Methods and comparisons. Chemomet. Intell. Lab. Syst. 72, 1 (2004), 57--71.Google Scholar
Cross Ref
- Gisle Bjontegaard. 2001. Calculation of Average PSNR Differences between RD-curves. Technical Report VCEG-M33. ITU-T Q. 6/SG16 VCEG.Google Scholar
- Frank Bossen. 2011. Common Test Conditions and Software Reference Configurations. Technical Report JCTVC-E700. Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11.Google Scholar
- Frank Bossen. 2012. Common Test Conditions and Software Reference Configurations. Technical Report JCTVC-J1100. Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11.Google Scholar
- BT.1788. 2007. Methodology for the subjective assessment of video quality in multimedia applications. Technical Report of the International Telecommunication Union.Google Scholar
- M. Naccari, K. Sharman, C. Rosewarne, B. Broass, and G. Sullivan. 2016. High Efficiency Video Coding (HEVC) Test Model 16 (HM 16) Improved Encoder Description Update 7. Technical Report JCTVC-Y1002. Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11.Google Scholar
- Yan-Qin Chen, Jin Duan, Yong Zhu, Xiao-Fei Qian, and Bo Xiao. 2015. Research on the image complexity based on neural network. In Proceedings of the International Conference on Machine Learning and Cybernetics (ICMLC’15), Vol. 1. IEEE, 295--300.Google Scholar
Cross Ref
- Hyomin Choi, Jonghun Yoo, Junghak Nam, Donggyu Sim, and Ivan V. Bajic. 2013. Pixel-wise unified rate-quantization model for multi-level rate control. IEEE J. Select. Topics Sig. Proc. 7, 6 (Dec. 2013), 1112--1123. DOI:https://doi.org/10.1109/JSTSP.2013.2272241Google Scholar
Cross Ref
- J. Corbera and S. Lei. 1997. Rate Control for Low-delay Video Communications. Technical Report Q15-A-20. ITU Study Group 16, Video Coding Experts Group, Portland.Google Scholar
- Rui Fan, Yongfei Zhang, and Bo Li. 2017. Motion classification-based fast motion estimation for high-efficiency video coding. IEEE Trans. Multimedia 19, 5 (May 2017), 893--907. DOI:https://doi.org/10.1109/TMM.2016.2642786Google Scholar
Digital Library
- Wei Gao, Sam Kwong, Hui Yuan, and Xu Wang. 2016. DCT coefficient distribution modeling and quality dependency analysis based frame-level bit allocation for HEVC. IEEE Trans. Circ. Syst. Vid. Technol. 26, 1 (Jan. 2016), 139--153. DOI:https://doi.org/10.1109/TCSVT.2015.2444671Google Scholar
Digital Library
- Wei Gao, Sam Kwong, Yu Zhou, and Hui Yuan. 2016. SSIM-based game theory approach for rate-distortion optimized intra frame CTU-level bit allocation. IEEE Trans. Multimedia 18, 6 (June 2016), 988--999. DOI:https://doi.org/10.1109/TMM.2016.2535254Google Scholar
Digital Library
- Jing He and Fuzheng Yang. 2017. Efficient frame-level bit allocation algorithm for H.265/HEVC. IET Image Proc. 11, 4 (Apr. 2017), 245--257. DOI:https://doi.org/10.1049/iet-ipr.2016.0166Google Scholar
Cross Ref
- Zhihai He, Yong Kwan Kim, and S. K. Mitra. 2001. Low-delay rate control for DCT video coding via rho;-domain source modeling. IEEE Trans. Circ. Syst. Vid. Technol. 11, 8 (Aug. 2001), 928--940. DOI:https://doi.org/10.1109/76.937431Google Scholar
- Bumshik Lee, Munchurl Kim, and Truong Q. Nguyen. 2014. A frame-level rate control scheme based on texture and nontexture rate models for high efficiency video coding. IEEE Trans. Circ. Syst. Vid. Technol. 24, 3 (Mar. 2014), 465--479. DOI:https://doi.org/10.1109/TCSVT.2013.2276880Google Scholar
- Bin Li, Houqiang Li, and Li Li. 2013. Adaptive Bit Allocation for R-lambda Model Rate Control in HM. Technical Report JCTVC-M0036. Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11.Google Scholar
- Bin Li, Houqiang Li, Li Li, and Jinlei Zhang. 2012. Rate Control by R-lambda Model for HEVC. Technical Report JCTVC-K0103. Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11.Google Scholar
- Bin Li, Houqiang Li, Li Li, and Jinlei Zhang. 2014. λ domain rate control algorithm for high efficiency video coding. IEEE Trans. Image Proc. 23, 9 (Sept. 2014), 3841--3854. DOI:https://doi.org/10.1109/TIP.2014.2336550Google Scholar
Cross Ref
- Li Li, Bin Li, Houqiang Li, and Chang Wen Chen. 2018. -domain optimal bit allocation algorithm for high efficiency video coding. IEEE Trans. Circ. Syst. Vid. Technol. 28, 1 (Jan. 2018), 130--142. DOI:https://doi.org/10.1109/TCSVT.2016.2598672Google Scholar
- Zhengguo Li, Feng Pan, Keng Pang Lim, Genan Feng, Xiao Lin, and Susanto Rahardja. 2003. Adaptive Basic Unit Layer Rate Control for JVT. Technical Report JVT-G012. Joint Video Team (JVT) of ISO/IEC MPEG 8 ITU-T VCEG.Google Scholar
- Hongwei Lin, Xiaohai He, Qi-Zhi Teng, Wenjie Fu, and Shuhua Xiong. 2016. Adaptive bit allocation scheme for extremely low-delay intraframe rate control in high efficiency video coding. J. Electron. Imag. 25, 4 (2016), 043008--043008.Google Scholar
Cross Ref
- Siwei Ma, Wen Gao, and Yan Lu. 2005. Rate-distortion analysis for H.264/AVC video coding and its application to rate control. IEEE Trans. Circ. Syst. Vid. Technol. 15, 12 (Dec. 2005), 1533--1544. DOI:https://doi.org/10.1109/TCSVT.2005.857300Google Scholar
Digital Library
- Zhaoqing Pan, Peng Jin, Jianjun Lei, Yun Zhang, Xingming Sun, and Sam Kwong. 2016. Fast reference frame selection based on content similarity for low complexity HEVC encoder. J. Vis. Commun. Image Rep. 40 (2016), 516--524.Google Scholar
Digital Library
- Zhaoqing Pan, Jianjun Lei, Yun Zhang, Xingming Sun, and Sam Kwong. 2016. Fast motion estimation based on content property for low-complexity H.265/HEVC encoder. IEEE Trans. Broadcast. 62, 3 (Sept. 2016), 675--684. DOI:https://doi.org/10.1109/TBC.2016.2580920Google Scholar
Cross Ref
- Zhaoqing Pan, Jianjun Lei, Yajuan Zhang, and Fu Lee Wang. 2018. Adaptive fractional-pixel motion estimation skipped algorithm for efficient HEVC motion estimation. ACM Trans. Multimedia Comput. Commun. Applic. 14, 1, Article 12 (Jan. 2018), 19 pages. DOI:https://doi.org/10.1145/3159170Google Scholar
Digital Library
- Mahsa T. Pourazad, Colin Doutre, Maryam Azimi, and Panos Nasiopoulos. 2012. HEVC: The new gold standard for video compression: How does HEVC compare with H.264/AVC? IEEE Cons. Electron. Mag. 1, 3 (July 2012), 36--46. DOI:https://doi.org/10.1109/MCE.2012.2192754Google Scholar
Cross Ref
- Liquan Shen, Ping An, Zhaoyang Zhang, Qianqian Hu, and Zhengchuan Chen. 2015. A 3D-HEVC fast mode decision algorithm for real-time applications. ACM Trans. Multimedia Comput. Commun. Applic. 11, 3, Article 34 (Feb. 2015), 23 pages. DOI:https://doi.org/10.1145/2700298Google Scholar
Digital Library
- Gary J. Sullivan, Jens Ohm, Woo-Jin Han, and Thomas Wiegand. 2012. Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circ. Syst. Vid. Technol. 22, 12 (Dec. 2012), 1649--1668. DOI:https://doi.org/10.1109/TCSVT.2012.2221191Google Scholar
Digital Library
- Yu-Kuang Tu, Jar-Ferr Yang, and Ming-Ting Sun. 2007. Rate-distortion modeling for efficient H.264/AVC encoding. IEEE Trans. Circ. Syst. Vid. Technol. 17, 5 (May 2007), 530--543. DOI:https://doi.org/10.1109/TCSVT.2007.894041Google Scholar
- Miaohui Wang, King Ngi Ngan, and Hongliang Li. 2015. An efficient frame-content based intra frame rate control for high efficiency video coding. IEEE Sig. Proc. Lett. 22, 7 (July 2015), 896--900. DOI:https://doi.org/10.1109/LSP.2014.2377032Google Scholar
Cross Ref
- Shanshe Wang, Siwei Ma, Shiqi Wang, Debin Zhao, and Wen Gao. 2013. Rate-GOP based rate control for high efficiency video coding. IEEE J. Select. Topics Sig. Proc. 7, 6 (Dec. 2013), 1101--1111. DOI:https://doi.org/10.1109/JSTSP.2013.2272240Google Scholar
Cross Ref
- Thomas Wiegand, Gary J. Sullivan, Gisle Bjontegaard, and Ajay Luthra. 2003. Overview of the H.264/AVC video coding standard. IEEE Trans. Circ. Syst. Vid. Technol. 13, 7 (July 2003), 560--576. DOI:https://doi.org/10.1109/TCSVT.2003.815165Google Scholar
Digital Library
- Mingliang Zhou, Yongfei Zhang, Bo Li, and Xupeng Lin. 2017. Complexity correlation-based CTU-level rate control with direction selection for HEVC. ACM Trans. Multimedia Comput. Commun. Applic. 13, 4, Article 53 (Aug. 2017), 23 pages. DOI:https://doi.org/10.1145/3107616Google Scholar
Digital Library
Index Terms
Frame-level Bit Allocation Optimization Based on<?brk?> Video Content Characteristics for HEVC
Recommendations
Optimal CTU-level bit allocation in HEVC for low bit-rate applications
AbstractThe coding efficiency of High Efficiency Video Coding (HEVC) outperforms all the past video coding standards. But for low bit-rate video applications, fewer bits cannot guarantee the reconstructed quality of each coding frame. Rate control is used ...
Region-based bit allocation and rate control for depth video in HEVC
In this paper, we present a novel rate control method with optimized region-based bit allocation for depth video coding. First, a synthetic view distortion oriented segmentation method is proposed to divide depth video into different regions, including ...
Rate control for non-uniform video in HEVC
A rate control method for Non-uniform video in HEVC is proposed.A global optimal bit allocation scheme is present.A new key frame classification and detection method is introduced. Rate control plays an important role in video coding, and most of the ...






Comments