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Joint Optimization for SSIM-Based CTU-Level Bit Allocation and Rate Distortion Optimization

2021-04-01 · Yang Li, Xuanqin Mou

Structural similarity (SSIM)-based distortion Dssim is more consistent with human perception than the traditional mean squared error Dmse. To achieve better video encoding quality, many studies on optimal bit allocation (OBA) used Dssim as the distortion metric. However, the MSE-based rate distortion optimization (RDO) was still used in these studies. The inconsistency between the optimization goals of OBA and RDO results in a non-optimal SSIM-based encoding performance. To solve this problem, we propose an accurate coding tree unit level Dssim-Dmse model, which enables performing the SSIM-based RDO with simpler R-Dmse cost scaled by the SSIM-based Lagrangian parameter λssim. Moreover, based on this model, the R-Dssim model can be accurately estimated based on the joint relationship of R-Dssim-λssim. With the accurate R-Dssim model, the SSIM-based OBA problem is then solved. Accordingly, the SSIM-based OBA and SSIM-based RDO are unified together in our scheme, called SOSR. Compared with the HEVC reference encoder HM16.20, SOSR saves 5%, 11%, and 17% bitrate under the same SSIM in the commonly used all-intra, hierarchical and non-hierarchical low-delay-B configurations, which is superior to existing state-of-the-art SSIM-based OBA schemes.

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Code (1)

yangli-xjtu/TBC-sosr 공식 구현

Tasks

Image Quality AssessmentSSIMVideo CompressionVideo Quality Assessment

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