Fast mode and depth decision HEVC intra prediction based on edge detection and partitioning reconfiguration
Fast mode and depth decision HEVC intra prediction based on edge detection and partitioning reconfiguration
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DOI：
10.1109/ispacs.2013.6704518
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发表时间：
2013-11
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影响因子：
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通讯作者：
Gaoxing Chen;Lei Sun;Zhenyu Liu;T. Ikenaga
中科院分区：
文献类型：
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作者：
Gaoxing Chen;Lei Sun;Zhenyu Liu;T. Ikenaga
高效视频编码（High Efficiency Video Coding， HEVC）是H.264的后继技术，是下一代视频压缩标准。为了提高视频帧的编码效率，HEVC的预测单元（PU）从4×4到64×64采用了35种帧内预测模式。然而，这种改进是以快速增加复杂性的代价为基础的。本文提出了一种基于边缘检测和重构的快速模式和深度决策算法，以缓解图像内预测中计算量大、精度下降小的问题。在模式判定中，提出了像素梯度统计（PGS）和模式细化（MR）。PGS在粗糙模式决策（Rough mode Decision， RMD）后，利用像素梯度信息辅助预测模式选择。磁共振利用相邻模态信息选择最可能模态（MPM）。在深度决策方面，提出了单元划分重构（UPR）方法。它将原有的分块顺序转换成更合理的结构，利用检测编码单元的平滑度来确定预测深度。平滑度检测基于PGS结果。实验结果表明，该方法可节省42.84%的编码时间，且编码增益降低很小（bdp -rate提高0.61%，BDPSNR降低0.041db）。与以往的工作相比，节省了时间，降低了效率损失。
High Efficiency Video Coding (HEVC), a successor to H.264, is the next generation video compression standard. To enhance the coding efficiency of video frames, 35 intra prediction modes adopted in Prediction Unit (PU) from 4×4 to 64×64 of HEVC. However the improvement is based on the cost of rapid increased complexity. This paper proposes a fast mode and depth decision algorithm based on edge detection and reconfiguration to alleviate the large computation complexity in intra prediction with the trivial degradation in the accuracy. In mode decision, pixel gradient statistics (PGS) and mode refinement (MR) is proposed. PGS use pixel gradient information to assist prediction mode selection after Rough Mode Decision (RMD). MR utilizes the neighboring mode information to select most probable mode (MPM). In depth decision, unit partitioning reconfiguration (UPR) is proposed. It exchanged the original partitioning order in a more reasonable structure, utilizes detecting the smoothness of coding unit to decide the prediction depth. Smoothness detecting is based on PGS result. Experiment result shows that the proposed method performs about 42.84% time saving with little degradation (BD-rate increase 0.61% and BDPSNR reduce 0.041db) in the coding gain. Comparing with previous work, it achieves more time saving and lesser efficiency loss.