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机构地区:[1]南京理工大学计算机科学与工程学院,江苏南京210000
出 处:《计算机应用与软件》2015年第12期101-104,共4页Computer Applications and Software
基 金:国家自然科学基金项目(61301106);江苏省自然科学基金项目(BK2012397);高等学校博士学科点专项科研基金项目(20123219120024);中央高校基本科研业务费专项资金项目(30920130121003);江苏省社会安全图像与视频理解重点实验室(南京理工大学)基金项目(30920130122006)
摘 要:HEVC(High Efficiency Video Coding)的编码性能足可以达到H.264/AVC的两倍。在帧内编码方面HEVC的性能提高主要来自于更精准的预测模式和更灵活的分块大小,同时带来了巨大的计算复杂度。为了大幅降低编码复杂度,提出的算法利用视频的局部纹理特性,首先用索贝尔算子提取当前编码单元CU(Coding Unit)的局部边界信息。分析边界信息后,停止不包含明显边界的CU的子块划分,对包含明显边界的CU快速选择预测方向为边界纹理方向。实验结果证明,提出的算法可以在视频质量基本不变的情况下,使帧内编码复杂度降低近一半。The coding performance of HEVC( High Efficiency Video Coding) is sufficient to double the performance of H. 264 / AVC. The improvement of HEVC performance in intra coding is mainly due to the more accurate prediction mode and more flexible blocking sizes,but these also demand huge computational complexity. In order to reduce the encoding complexity significantly,we proposed an algorithm which uses local texture characteristic of video. Firstly it extracts the local boundary information in current CU( coding unit) with Sobel operator.After analysing the local boundary information,the proposed algorithm stops the partitioning of those CU sub-blocks without clear boundaries,and for those CUs containing clear boundaries it makes fast selection of the boundary texture direction as their predicting direction.Experimental results showed that the proposed algorithm was able to reduce the intra coding complexity by nearly half while keeping the quality of the video almost the same.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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