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A CNN-Based Optimal CTU λ Decision for HEVC Intra Rate Control

Lili WEI, Zhenglong YANG, Zhenming WANG, Guozhong WANG

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Summary :

Since HEVC intra rate control has no prior information to rely on for coding, it is a difficult work to obtain the optimal λ for every coding tree unit (CTU). In this paper, a convolutional neural network (CNN) based intra rate control is proposed. Firstly, a CNN with two last output channels is used to predict the key parameters of the CTU R-λ curve. For well training the CNN, a combining loss function is built and the balance factor γ is explored to achieve the minimum loss result. Secondly, the initial CTU λ can be calculated by the predicted results of the CNN and the allocated bit per pixel (bpp). According to the rate distortion optimization (RDO) of a frame, a spatial equation is derived between the CTU λ and the frame λ. Lastly, The CTU clipping function is used to obtain the optimal CTU λ for the intra rate control. The experimental results show that the proposed algorithm improves the intra rate control performance significantly with a good rate control accuracy.

Publication
IEICE TRANSACTIONS on Information Vol.E104-D No.10 pp.1766-1769
Publication Date
2021/10/01
Publicized
2021/07/19
Online ISSN
1745-1361
DOI
10.1587/transinf.2021EDL8047
Type of Manuscript
LETTER
Category
Image Processing and Video Processing

Authors

Lili WEI
  Shanghai University of Engineering Science
Zhenglong YANG
  Shanghai University of Engineering Science
Zhenming WANG
  Shanghai Branch of Communication Information Group Co., Ltd
Guozhong WANG
  Shanghai University of Engineering Science

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