基于视觉感知的率失真优化算法

A rate-distortion optimization algorithm based on visual perception

率失真优化在视频编码中起着关键作用,其目的是在压缩效率和视频质量失真之间取得平衡。现有的率失真算法主要针对视频中时间和空间冗余的消除,未充分考虑视频内容的主观感知冗余。本文提出了一种基于视觉感知的率失真优化算法,通过数据驱动的JND预测模型推导拉格朗日乘数因子,并使用显著性模型优化拉格朗日乘子权重系数,最终融合应用于率失真优化,并采用SW-SSIM评估视频质量,实现视频编码的感知优化。实验结果表明,与AVS3标准率失真算法相比,本文所提算法平均节省12.15%的码率,SW-SSIM提高了0.004 3,有效降低了视频内容中的感知冗余,提高了视频感知质量和编码性能。

The rate-distortion optimization plays a key role in video coding,which aims to achieve a tradeoff between compression efficiency and video quality distortion.The existing rate-distortion optimization algorithms mainly aim to eliminate time and space redundancy,which ignore subjective perception of video content and result in a large amount of perceptual redundancy in video.To address these issues,a rate distortion algorithm based on visual perception is proposed in this article.Firstly,the Lagrangian multiplier factor is obtained based on the data-driven just noticeable distortion prediction mode,which is more in line with the perception of the human eye.Secondly,the Lagrangian multiplier weight coefficient is based on salient model.Finally,the fusion of two models is applied to rate-distortion optimization,and SW-SSIM is used to evaluate video quality and achieve perceptual video coding optimization.Compared with the third generation audio and video coding standard algorithm,experimental results show that the proposed algorithm reduces bitrate by 12.15% averagely,and the salience weighted-structural similarity index metric increases by 0.004 3.Furthermore,the proposed algorithm reduces the perceptual redundancy in video content,and improves the video perceptual quality and coding performance.