现代电子技术2024，Vol.47Issue(11)：69-77,9.DOI:10.16652/j.issn.1004-373x.2024.11.013
基于卷积神经网络的HEVC帧内预测算法优化
HEVC intra-frame prediction algorithm optimization based on CNN
摘要
Abstract
As one of the most fundamental and crucial technologies in the HEVC(high efficiency video coding)standard,intra-frame prediction plays a crucial role in achieving high speed,high quality and high compression efficiency in video coding.This paper addresses the complexity issue of intra-frame prediction and proposes a method based on deep convolutional neural networks(CNNs)to predict CTU(coding tree unit)partition by learning,thereby reducing the complexity of HEVC intra-frame coding.By establishing a large-scale CTU partition database and using the learning capability of CNN to study various CTU partition patterns,the CTU partition is predicted accurately,so as to avoid the traditional exhaustive searches,reduce the complexity of HEVC encoding significantly and improve the coding efficiency.Experimental results demonstrate that the proposed method reduces intra-frame coding time by 62.25%and 69.06%for the test sequences and the images,respectively.In comparison with the other advanced methods,its bitrate increases by only 2.12%and 1.13%,which achieves the purpose of optimization.关键词
高效视频编码/帧内预测编码/卷积神经网络/深度学习/编码单元/深度决策/编码块分割Key words
HEVC/intra-frame predictive coding/CNN/deep leaning/coding unit/depth decision/coding block segmentation分类
信息技术与安全科学引用本文复制引用
李轩,冷雨馨..基于卷积神经网络的HEVC帧内预测算法优化[J].现代电子技术,2024,47(11):69-77,9.基金项目
辽宁省"兴辽英才计划"项目(XLYC1907022) （XLYC1907022）
辽宁省重点研发计划项目(2020JH2/10100045) （2020JH2/10100045）
