Foreground motion and spatial saliency-based efficient HEVC Video Coding

Abstract

High Efficiency Video Coding (HEVC) could not provide real time facilities to the limited processing and battery powered electronic devices as its encoding time complexity increases multiple times compared to its predecessor. Numerous researchers contribute to address this limitation by reducing a number of motion estimation (ME) modes where they analyze homogeneity, residual and statistical correlation among different modes. Although their approaches save some encoding time, however, could not reach the similar rate-distortion (RD) performance with HEVC encoder as they merely depend on existing Lagrangian cost function (LCF) within HEVC framework. To overcome this limitation, in this paper, we capture visual attentive Foreground motion and salient region (FMSR) which are sensitive to human visual system for quality assessment. The FMSR features captured by visual attentive and dynamic background modeling are adaptively synthesized to determine a subset of candidate modes. This preprocessing phase is independent from LCF. Since the proposed technique can avoid exhaustive exploration of all modes with simple criteria, it can reduce 27% encoding time on average. With efficient selection of FMSR-based appropriate block partitioning modes, it can also improve up to 1.0dB peak signal-to-noise ratio (PSNR).