基于预测划分卷积神经网络的全景视频快速编码算法

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Fast coding algorithm based on predictive partition convolutional neural network for 36O-degree video

Xiang Hai，Chen Fen ↑ ，Qin Yiqing，LiXu，Peng Zongju （SchoolofElectrical&ElectronicEnginering，Chongqing UniversityofTechnology，Chongqing 40oo54，China）

Abstract：Inorder tosolve theproblem of excessive complexityof360-degree video basedonequirectangularprojection （ERP）of versatile videocoding（VVC），thispaperproposedafast CU partitionalgorithmbasedonpredictivepartitionconvolutionaleuralnetwork（PP-CNN）.Firstly，this paperanalyzed thepartition characteristicsofCUsof ERP360-degree video indierentlatituderegionsandintroducedthelatitudefeatureinthisproposedalgorithm.Secondly，thealgorithmestablished 360-degree videodatasetwiththecharacteristicsoflatitudeandquantizationparameters.Then，this methoddesignedalightweightPP-CNN model topredicttheedgedivision informationofCUs.Next，thealgorithm basedontheoutputof PP-CNN modeldevelopedadual-thresholdCUfastpartitiondecisionschemetoremoveredundantpartitionpaterns.Finaly，thispaper designed threedecisionmodes，fast，balancedandperformanceaccording totheneeds ofcoding scenarios.Theextensive experimental results show that the proposed algorithm is able to shorten the coding time by 39.31%～61.95% on average under the full intra-frame coding configuration at the BDBR increases by only 0.37%～1 43% compared with the official testbed VTM-14.O-36olib13.1，indicatingthatthealgorithmcanrealizefastercoding speedunderthepremiseof guaranteeingcoding performance.

Keywords：ERP36O-degreevideo；latitude；CUpartition；PP-CNN

0 引言

随着通信技术和多媒体技术的快速发展，超高清视频逐渐成为人们主流的观看选择。（剩余13978字）