The SSIM-based rate distortion optimization (R-DO) has been proved to be an effective way to promote the perceptual video coding performance, and the Lagrange multiplier decision is the key to the SSIM-based RD-optimized video coding.

Through extensively analyzing the characteristics of SSIM-based and SSE-based video distortions, researchers from the Institute of Acoustics, Chinese Academy of Sciences (IACAS) propose a low-complexity content-adaptive SSIM-based Lagrange multiplier decision method for perceptual video coding.

The proposed method first estimates frame-level SSIM-based Lagrange multiplier by scaling the traditional SSE-based Lagrange multiplier with the ratio of SSE-based distortion to SSIM-based distortion. Via predicting the macroblock’s perceptual importance in the whole frame, the macroblock-level Lagrange multiplier is further refined to promote the accuracy of the Lagrange multiplier decision.

To verify the effectiveness of the proposed method, the method on the H.264/AVC reference software JM16.1 is implemented. Besides, the coding structure “IPPP” and the “baseline profile” are adopted in the experiments. Experimental results show that the proposed method can obtain almost the same rate-SSIM performance and subjective quality as the state-of-the-art SSIM-based RD-optimized video coding methods with lower computation overheads.

Fig.1 Performance comparison of the proposed RDO to the traditional RDO (Image by IACAS).