SSIM based perceptual distortion rate optimization coding The current rate distortion optimization (RDO) coding schemes usually use the Sum of Absolute Difference (SAD) or Sum of Square Difference (SSD) as the distortion metric. However, neither SAD nor SSD correlates with the human visual system (HVS) very well. To develop a perceptual distortion based video encoder, we employ the Structural Similarity (SSIM) Index as the distortion metric and propose a SSIM based Lagrangian perceptual distortion rate optimization (PDRO) method in this paper. Furthermore, to adapt the different input sequences dynamically, we present an adaptive Lagrange multiplier selection scheme based on the properties of the input sequences. By modeling the transformed residuals with Laplace distribution, the statistical SSIM and rate models are deduced to obtain the adaptive Lagrange multiplier. Extensive experiments show that the proposed scheme can achieve better perceptual distortion rate performance and provide better visual quality than the SADSSD based RDO coding scheme.

JNDbased Perceptual Rate Distortion Optimization for AV1 Encoder AV1 is the nextgeneration open video coding format, and it can achieve significant coding efficiency with novel coding tools. It supports Lagrangian rate distortion optimization (RDO) method to optimize the coding performance. However, the distortion and the Lagrangian multiplier used in RDO ignore the characteristics of human visual system (HVS), which leads to insufficiency for perceptual video coding. To solve this problem, a perceptual RDO scheme based on the Just Noticeable Distortion (JND) threshold of HVS is proposed. The JND for each pixel is first measured according to three perceptual features: luminance adaptation, masking effects and structure sensitivity. Based on the observation that the regions with smaller distortion visibility thresholds are more sensitive to HVS, a JNDbased Lagrangian multiplier is derived to adaptively adjust the ratedistortion (RD) performance for each coding block. Experiments demonstrate that the proposed method can achieve an average SSIMbased xe2x88x923.93% BDRate saving compared with the original AV1 encoder, which effectively improve the coding performance.