结合卷积神经网络的HEVC帧内编码压缩改进算法

王婷; 何小海; 孙伟恒; 熊淑华; Karn Pradeep

doi:doi:10.11805/tkyda2019065

太赫兹科学与电子信息学报, 2020, 18 (2): 291, 网络出版: 2020-05-28

结合卷积神经网络的HEVC帧内编码压缩改进算法

Improved HEVC intra coding compression algorithm combined with convolutional neural network

论文大纲

王婷何小海 ^*孙伟恒熊淑华 Karn Pradeep

作者单位

四川大学电子信息学院，四川成都 610065

卷积神经网络集成高效视频编码下采样 Convolutional Neural Network integrated HEVC down-sampling

摘要

近年来，卷积网络深度学习已在图像处理、目标检测等领域取得巨大成功。受其启发，将卷积神经网络(CNN)应用于传统视频压缩标准已成为一个新的研究热点。本文提出一种集成卷积神经网络的高效视频编码(HEVC)压缩改进算法，将下采样过程、HEVC的编解码过程、上采样及质量增强过程集成为一体。为高效提取视频帧的结构特征，在所提压缩算法中集成了两个卷积神经网络。提出了一种下采CNN(DwSCNN)代替双三次下采，在有效降低分辨率的同时保留细节信息，得到更为紧凑的低分辨率视频序列，将此低分辨率视频序列通过HEVC帧内编码进行进一步的数据量压缩，通过提出一个质量增强CNN(PPCNN)来改善解码后恢复到原始分辨率的降质视频序列。实验结果显示，本文压缩改进算法在低码率段与标准HEVC相比，能达到更好的质量重建，并且在接近一致的PSNR值时，能节省39.46%的时间和11.04%的比特率，本文算法的视频压缩性能优于HEVC标准算法和相关文献方法。

Abstract

In recent years, deep learning of convolutional networks has achieved great success in the fields of image processing and target detection. It has become a new research hotspot to apply Convolutional Neural Networks(CNN) to traditional video compression standards. An improved High Efficiency Video Coding(HEVC) compression algorithm integrated with convolutional neural network is proposed, which integrates down-sampling, HEVC codec, up-sampling and quality enhancement process. In order to extract the structural features of video frames efficiently, two convolutional neural networks are integrated in the proposed compression algorithm. Down Sampling CNN(DwSCNN) replaces bicubic down-sampling, which preserves the detailed information while reducing the resolution, obtaining a more compact low resolution video sequence. The low-resolution video sequence is further compressed by HEVC intra coding, and a quality-enhanced Post Processing CNN(PPCNN) is proposed to improve the degraded video sequence that is restored to the original resolution after decoding. The experimental results show that the proposed compression improvement algorithm can achieve better quality reconstruction than the standard HEVC in the low code rate segment, and can save time by 39.46% and bit rate by 11.04% when the PSNR value is close to the same. The video compression performance of the algorithm is superior to the HEVC standard algorithm and other related literature methods.

参考文献

[1] 1668.

SULLIVAN G J,OHM J,HAN W,et al. Overview of the High Efficiency Video Coding (HEVC) standard[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012,22(12):1649- 1668.

SULLIVAN G J,OHM J,HAN W,et al. Overview of the High Efficiency Video Coding (HEVC) standard[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012,22(12):1649-

[2] CHEN H G,HE X H,MA M L,et al. Low bit rates image compression via adaptive block down-sampling and super resolution[J]. Journal of Electronic Imaging, 2016,25(1):013004.

CHEN H G,HE X H,MA M L,et al. Low bit rates image compression via adaptive block down-sampling and super resolution[J]. Journal of Electronic Imaging, 2016,25(1):013004.

[3] DONG J,YE Y. Adaptive down-sampling for high-definition video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2014,24(3):480-488.

DONG J,YE Y. Adaptive down-sampling for high-definition video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2014,24(3):480-488.

[4] LI C,SONG L,XIE R,et al. CNN based post-processing to improve HEVC[C]// 2017 IEEE International Conference on Image Processing. Beijing,China:IEEE, 2017:4577-4580.

LI C,SONG L,XIE R,et al. CNN based post-processing to improve HEVC[C]// 2017 IEEE International Conference on Image Processing. Beijing,China:IEEE, 2017:4577-4580.

[5] YANG R,XU M,WANG Z L,et al. Multi-frame quality enhancement for compressed video[C]// 2018 IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City,UT,USA:IEEE, 2018:6664-6673.

YANG R,XU M,WANG Z L,et al. Multi-frame quality enhancement for compressed video[C]// 2018 IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City,UT,USA:IEEE,

2018:6664-6673.

YANG R,XU M,WANG Z L,et al. Multi-frame quality enhancement for compressed video[C]// 2018 IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City,UT,USA:IEEE, 2018:6664-6673.

[6] LI X Q,HE X H,QING L B,et al. Research on compression performance of ultrahigh-definition videos[J]. Journal of Electronic Imaging, 2017,26(6):063008.

LI X Q,HE X H,QING L B,et al. Research on compression performance of ultrahigh-definition videos[J]. Journal of Electronic Imaging, 2017,26(6):063008.

[7] TAO W,JIANG F,ZHANG S P,et al. An end-to-end compression framework based on convolutional neural networks[C]// 2017 Data Compression Conference. Snowbird,UT,USA:IEEE, 2017:463.

TAO W,JIANG F,ZHANG S P,et al. An end-to-end compression framework based on convolutional neural networks[C]// 2017 Data Compression Conference. Snowbird,UT,USA:IEEE, 2017:463.

[8] YANG R,XU M,LIU T,et al. Enhancing quality for HEVC compressed videos[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2019,29(7):2039-2054.

YANG R,XU M,LIU T,et al. Enhancing quality for HEVC compressed videos[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2019,29(7):2039-2054.

[9] CHRISTIAN S,LIU W,JIA Y Q,et al. Going deeper with convolutions[C]// 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston,MA,USA:IEEE, 2015:1–9.

CHRISTIAN S,LIU W,JIA Y Q,et al. Going deeper with convolutions[C]// 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston,MA,USA:IEEE, 2015:1–9.

[10] HE K M,ZHANG X Y,REN S Q,et al. Identity mappings in deep residual networks[C]// 2016 European Conference on Computer Vision. Amsterdam,Netherland:IEEE, 2016:630–645.

HE K M,ZHANG X Y,REN S Q,et al. Identity mappings in deep residual networks[C]// 2016 European Conference on Computer Vision. Amsterdam,Netherland:IEEE, 2016:630–645.

[11] ARBELAEZ P,MAIRE M,FOWLKES C,et al. Contour detection and hierarchical image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33(5):898-916.

ARBELAEZ P,MAIRE M,FOWLKES C,et al. Contour detection and hierarchical image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33(5):898-916.

[12] 2018:1-3.

LEE Y W,KIM J H,CHOI Y J,et al. CNN-based approach for visual quality improvement on HEVC[C]// 2018 IEEE International Conference on Consumer Electronics. Las Vegas,NV,USA:IEEE, 2018:1-3.

LEE Y W,KIM J H,CHOI Y J,et al. CNN-based approach for visual quality improvement on HEVC[C]// 2018 IEEE International Conference on Consumer Electronics. Las Vegas,NV,USA:IEEE,

[13] 2014:675–678.

JIA Y Q,SHELHAMER E,DONAHUE J,et al. Caffe: convolutional architecture for fast feature embedding[C]// 2014 ACM International Conference on Multimedia. Orlando,Florida,USA:ACM, 2014:675–678.

JIA Y Q,SHELHAMER E,DONAHUE J,et al. Caffe: convolutional architecture for fast feature embedding[C]// 2014 ACM International Conference on Multimedia. Orlando,Florida,USA:ACM,

[14] KINGMA D P,BA J L. Adam: a method for stochastic optimization[C]// 2015 International Conference for Learning Representations. San Diego,CA,USA:[s.n.], 2015:1-15.

KINGMA D P,BA J L. Adam: a method for stochastic optimization[C]// 2015 International Conference for Learning Representations. San Diego,CA,USA:[s.n.], 2015:1-15.

[15] KIM J,LEE J K,LEE K M. Accurate image super-resolution using very deep convolutional networks[C]// 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas,NV,USA:IEEE, 2016:1646-1654.

KIM J,LEE J K,LEE K M. Accurate image super-resolution using very deep convolutional networks[C]// 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas,NV,USA:IEEE, 2016:1646-1654.

王婷, 何小海, 孙伟恒, 熊淑华, Karn Pradeep. 结合卷积神经网络的HEVC帧内编码压缩改进算法[J]. 太赫兹科学与电子信息学报, 2020, 18(2): 291. WANG Ting, HE Xiaohai, SUN Weiheng, XIONG Shuhua, Karn Pradeep. Improved HEVC intra coding compression algorithm combined with convolutional neural network[J]. Journal of terahertz science and electronic information technology, 2020, 18(2): 291.

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