| 杨骁,滕国伟,李国平,赵海武,王国中,安平.基于自适应深度预测的快速变换单元判决算法[J].光电子激光,2014,(9):1785~1790 |
| 基于自适应深度预测的快速变换单元判决算法 |
| Fast transform unit decision algorithm based on adaptive depth prediction |
| 投稿时间：2014-05-06 |
| DOI： |
| 中文关键词: 残差四叉树(RQT) 自适应 时空相关性 复杂度 |
| 英文关键词:residual quadratic tree (RQT) adaptive temporal-spatial correlation complexi ty |
| 基金项目:国家自然科学基金资助(61271212,61172096)、上海市自然科学基金(14ZR1415200)和新型显示教育部重点实验室开放课题资助项目 (上海大学 通信与信息工程学院,上海 200072) |
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| 中文摘要: |
| 新一代视频编码标准HEVC相比之前标准,在提升编 码效率的同时显著增加计算复杂度。针对这一问题,本文提出了 一种基于自适应深度预测的快速变换单元(TU)判决算法,利用残差四叉树(RQT)深度自身分 布特点以及时空相邻 RQT最大深度的相关性预测不同尺寸编码单元(CU)的RQT深度,跳过不必要的深度计算。仿真 结 果表明,在标准编码配置条件下,相比全部深度判决方法,本算法在保证编码效果的前提下 ,平均降低50%的TU运算时间,极大减少计算复杂度；同时相比于同类算法 在处理复杂序列 时的低效率,本算法很好地解决了此类问题。 |
| 英文摘要: |
| The emerging high efficiency video coding (HEVC) standard uses residua l quadratic tree (RQT) to transform and quantize the predicted residuals after motion estimation (ME).Rate-distortion costs of all the nodes at different RQT depths are compared transversally to sel ect the optimal one or we call it the optimal transform unit (TU).The coding efficiency is improved si gnificantly by the new transform technology.However,huge computation complexity is introduced compare d with previous standard.To solve the above problem,a rapid TU mode decision algorithm is propos ed in this paper focusing on adaptive depth prediction.First of all,weights of temporal-spatia l adjacent CTUs combined with characteristics of RQT depth distribution themselves are used to p redict RQT depth of certain CTU/CUs.The RQT depths of rest CTU/CUs are predicted via temporal-spati al correlation between RQT maximum depths.As a result,unnecessary RQT depth can be skipped or terminated. According to simulation results,conclusions are obtained that the TU computatio n complexity can be reduced by about 50% under standard coding configuration,while maintaining almos t the same RD performance as original standard.Our algorithm reduces TU computation complexit y greatly as expected.Meanwhile,the proposed algorithm effectively addresses the low effici ency problem under complex sequences met by other related algorithms. |
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