Changchun Institute of Optics,Fine Mechanics and Physics,CAS
Fast prediction unit selection method for HEVC intra prediction based on salient regions | |
Feng, L.; M. Dai; C.-l. Zhao and J.-y. Xiong | |
2016 | |
发表期刊 | Optoelectronics Letters |
卷号 | 12期号:4 |
摘要 | In order to improve the prediction speed of HEVC encoder, this paper proposed an algorithm of PU size decision based on information entropy for HEVC (High Efficiency Video Coding) intra prediction. This algorithm mainly utilizes the characteristic of image entropy producing different values with the richness of the image detail to decide whether the PUs need segmentation. Firstly, we calculate the information entropy of every LCU, then we can obtain the optimal partition size from the PU size of 6464 to 44, so that the optimal coding depth is acquired, we can make the intra angular prediction in the optimal coding depth. The experimental results show that we can avoid the unnecessary RD cost calculating process in the traversal search mode, and the coding time was reduced by about 22.6% in the promise of coding performance essentially unchanged. This algorithm simplified the unnecessary rate-distortion cost procedure in traversal search mode, shortened the intra prediction coding time at high image quality level. 2016, Editorial Board of Journal of Harbin Institute of Technology. All right reserved. |
文章类型 | 期刊 |
收录类别 | EI |
语种 | 中文 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ciomp.ac.cn/handle/181722/56913 |
专题 | 中科院长春光机所知识产出 |
推荐引用方式 GB/T 7714 | Feng, L.,M. Dai,C.-l. Zhao and J.-y. Xiong. Fast prediction unit selection method for HEVC intra prediction based on salient regions[J]. Optoelectronics Letters,2016,12(4). |
APA | Feng, L.,M. Dai,&C.-l. Zhao and J.-y. Xiong.(2016).Fast prediction unit selection method for HEVC intra prediction based on salient regions.Optoelectronics Letters,12(4). |
MLA | Feng, L.,et al."Fast prediction unit selection method for HEVC intra prediction based on salient regions".Optoelectronics Letters 12.4(2016). |
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Fast prediction unit(805KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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