Visual saliency based perceptual video coding in HEVC

Henglu Wei, Xin Zhou, Wei Zhou, Chang Yan, Zhemin Duan, Nana Shan

Abstract: Perceptual video coding has the potential to provide the same visual quality at a lower bit-rate, compared with the traditional objective quality based scheme. Visual saliency represents the probability of human attention over frames, and it is used for allocating coding bits or controlling visual quality. In this paper, a HEVC compliant perceptual video coding scheme is proposed based on visual saliency. At first visual saliency map is attained to indicate the distribution of saliency. Then refined distortion allocating method is performed in CU level with adaptive QP which is adjusted by the average visual saliency. Besides, a fast CU mode decision algorithm suitable for perceptual video coding in HEVC is proposed to accelerate the encoder. In the fast algorithm, the average saliency is used to estimate texture complexity and movements in videos. Experimental results show that up to 22.52% bit-rate and 43.48% encoding time can be saved by our methods with negligible perceptual quality loss.