The recent High Efficiency Video Coding (HEVC) Standard demonstrates higher rate-distortion (RD) performance compared to its predecessor H.264/AVC using different new tools especially larger and asymmetric intermode variable size motion estimation and compensation. This requires more than 4 times computational time compared to H.264/AVC. As a result it has always been a big concern for the researchers to reduce the amount of time while maintaining the standard quality of the video. The reduction of computational time by smart selection of the appropriate modes in HEVC is our motivation. To accomplish this task in this paper, we use phase correlation to approximate the motion information between current and reference blocks by comparing with a number of different binary pattern templates and then select a subset of motion estimation modes without exhaustively exploring all possible modes. The experimental results exhibit that the proposed HEVC-PC (HEVC with Phase Correlation) scheme outperforms the standard HEVC scheme in terms of computational time while preserving-the same quality of the video sequences. More specifically, around 40% encoding time is reduced compared to the exhaustive mode selection in HEVC.

The emerging High Efficiency Video Coding (HEVC) standard introduces a number of innovative and powerful coding tools to acquire better compression efficiency compared to its predecessor H.264. The encoding time complexities have also increased multiple times that is not suitable for realtime video coding applications. To address this limitation, this paper employs a novel coding strategy to reduce the time complexity in HEVC encoder by efficient selection of appropriate block-partitioning modes based on human visual features (HVF). The HVF in the proposed technique comprise with human visual attention modelling-based saliency feature and phase correlation-based motion features. The features are innovatively combined through a fusion process by developing a content-based adaptive weighted cost function to determine the region with dominated motion/saliency (RDMS)- based binary pattern for the current block. The generated binary pattern is then compared with a codebook of predefined binary pattern templates aligned to the HEVC recommended block-paritioning to estimate a subset of inter-prediction modes. Without exhaustive exploration of all modes available in the HEVC standard, only the selected subset of modes are motion estimated and motion compensated for a particular coding unit. The experimental evaluation reveals that the proposed technique notably down-scales the average computational time of the latest HEVC reference encoder by 34% while providing similar rate-distortion (RD) performance for a wide range of video sequences.

No abstract

No abstract

No abstract