Telecommunications Science ›› 2019, Vol. 35 ›› Issue (2): 59-69.doi: 10.11959/j.issn.1000-0801.2019025

• research and development • Previous Articles     Next Articles

Omni directional video coding rate distortion optimization method based on weighted-to-spherically-uniform structural similarity

Yufeng ZHOU,Mei YU,Baozhen DU,Yang SONG,Gangyi JIANG   

  1. Faculty of Information Science and Engineering,Ningbo University,Ningbo 315211,China
  • Revised:2019-01-21 Online:2019-02-01 Published:2019-02-23
  • Supported by:
    The National Natural Science Foundation of China(61671258);The National Natural Science Foundation of China(61871247);The Natural Science Foundation of Zhejiang Province of China(LY15F010005)

Abstract:

Aiming at the shortcomings of the coding rate distortion model in traditional video coding,considering the characteristics of equal rectangular omnidirectional video,a method of omnidirectional video coding rate distortion optimization based on spherical weighted structural similarity (WS-SSIM) was proposed.By considering the distortion of the internal structural similarity of the projection plane and the relationship between the spherical distortion and the projection plane distortion,the “spherical weighted structural similarity” was proposed to describe the degree of distortion of the planar omnidirectional image local block relative to the viewing sphere,which was applied to the rate-distortion optimization process of omnidirectional video coding and adaptive selection of quantization parameters to improve vision-based coding efficiency.The experimental results show that compared with the HEVC video coding standard HM16.9 test platform,the proposed method can save an average of 24.48% code rate under the same visual quality,which indicates that the method has significant performance for improving the omnidirectional video coding rate distortion performance.

Key words: omnidirectional video coding, weighted-to-spherically-uniform structural similarity, rate distortion optimization, adaptive quantization parameter selection

CLC Number: 

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