{"title":"基于端到端边缘检测网络的深度图快速编码算法","authors":"Chang Liu, Ke-bin Jia, Pengyu Liu","doi":"10.1109/VCIP49819.2020.9301859","DOIUrl":null,"url":null,"abstract":"Compared with traditional High Efficiency Video Coding (HEVC), 3D-HEVC introduces multi-view coding and depth map coding, which leads to significant increase in coding complexity. In this paper, we propose a low complexity intra coding algorithm for depth map based on end-to-end edge detection network. Firstly, we use Holistically Nested Edge Detection (HED) network to determine the edge location of the depth map. Secondly, we use Ostu method to divide the output of the HED into foreground region and background region. Finally, the CU size and the candidate list of intra mode are determined according to the region of coding tree unit (CTU). Experimental results demonstrate that the proposed algorithm can reduce the encoding time by 39.56% on average under negligible degradation of coding performance.","PeriodicalId":431880,"journal":{"name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fast Intra Coding Algorithm for Depth Map with End-to-End Edge Detection Network\",\"authors\":\"Chang Liu, Ke-bin Jia, Pengyu Liu\",\"doi\":\"10.1109/VCIP49819.2020.9301859\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compared with traditional High Efficiency Video Coding (HEVC), 3D-HEVC introduces multi-view coding and depth map coding, which leads to significant increase in coding complexity. In this paper, we propose a low complexity intra coding algorithm for depth map based on end-to-end edge detection network. Firstly, we use Holistically Nested Edge Detection (HED) network to determine the edge location of the depth map. Secondly, we use Ostu method to divide the output of the HED into foreground region and background region. Finally, the CU size and the candidate list of intra mode are determined according to the region of coding tree unit (CTU). Experimental results demonstrate that the proposed algorithm can reduce the encoding time by 39.56% on average under negligible degradation of coding performance.\",\"PeriodicalId\":431880,\"journal\":{\"name\":\"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP49819.2020.9301859\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP49819.2020.9301859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
与传统的高效视频编码(High Efficiency Video Coding, HEVC)相比,3D-HEVC引入了多视图编码和深度图编码,使得编码复杂度显著提高。本文提出了一种基于端到端边缘检测网络的低复杂度深度图内编码算法。首先,我们使用整体嵌套边缘检测(HED)网络确定深度图的边缘位置。其次,利用Ostu方法将HED的输出分割为前景区域和背景区域;最后,根据编码树单元(CTU)的区域确定CU大小和内模候选列表。实验结果表明,该算法在编码性能下降可以忽略不计的情况下,平均减少了39.56%的编码时间。
Fast Intra Coding Algorithm for Depth Map with End-to-End Edge Detection Network
Compared with traditional High Efficiency Video Coding (HEVC), 3D-HEVC introduces multi-view coding and depth map coding, which leads to significant increase in coding complexity. In this paper, we propose a low complexity intra coding algorithm for depth map based on end-to-end edge detection network. Firstly, we use Holistically Nested Edge Detection (HED) network to determine the edge location of the depth map. Secondly, we use Ostu method to divide the output of the HED into foreground region and background region. Finally, the CU size and the candidate list of intra mode are determined according to the region of coding tree unit (CTU). Experimental results demonstrate that the proposed algorithm can reduce the encoding time by 39.56% on average under negligible degradation of coding performance.