基于梯度的H.265/HEVC帧内预测硬件加速算法研究

A gradient-based H.265/HEVC intra prediction hardware acceleration algorithm

HEVC即H.265,是目前最新的视频编码标准。相比于前一代视频编码标准,H.265/HEVC虽然能够明显改善视频压缩效率,但是却带来了更高的计算复杂度,尤其是在帧内预测过程中。为了解决这个问题,提出一种基于梯度的帧内预测硬件加速算法来跳过一些帧内预测模式和划分深度的预测过程,从而达到减少计算的目的。利用图像梯度信息来粗略估计编码单元的纹理方向和纹理复杂度,其中纹理方向用来估计编码单元的最优帧内预测方向,纹理复杂度用来判断是否跳过当前划分深度的预测编码过程。实验表明,相比于H.265/HEVC测试模型HM16.18,本文提出的算法能够减少60.59%的编码时间,仅造成0.38dB的BD-PSNR减少和8.52%的BD-Rate增加。

High efficiency video coding (HEVC), namely H.265, is the latest video coding standard. Compared to the previous generation of video coding standards, H.265/HEVC can significantly improve video compression efficiency. However, it incurs a much higher computational complexity, especially in the intra prediction process. To address this issue, we propose an improved and hardware-friendly gradient-based intra prediction hardware acceleration algorithm which can skip some of the intra prediction modes and the intra prediction process for depth partition, so as to reduce computation. The proposed algorithm can estimate the texture direction and texture complexity of coding-units according to gradient information. The texture direction can be used to estimate the optimal intra prediction direction of the coding-unit, and the texture complexity can determine whether to skip the intra-prediction process for the current depth partitioning. Experimental results show that compared with the HEVC test model HM16.18, the proposed algorithm can reduce encoding time by 60.59%, with only 8.52% BD-rate increase and 0.38dB BD-PSNR decrease.