Linwei Zhu, Yun Zhang, N. Li, Jinyong Pi, Xinju Wu
{"title":"Sparse Representation-Based Intra Prediction for Lossless/Near Lossless Video Coding","authors":"Linwei Zhu, Yun Zhang, N. Li, Jinyong Pi, Xinju Wu","doi":"10.1109/VCIP49819.2020.9301752","DOIUrl":null,"url":null,"abstract":"In this paper, a novel intra prediction method is presented for lossless/near lossless High Efficiency Video Coding (HEVC), termed as Sparse Representation based Intra Prediction (SRIP). In specific, the existing Angular Intra Prediction (AIP) modes in HEVC are organized as a mode dictionary, which is utilized to sparsely represent the visual signal by minimizing the difference with respect to the ground truth. For the match of encoding and decoding, the sparse coefficients are also required to be encoded and transmitted to the decoder side. To further improve the coding performance, an additional binary flag is included in the video codec to indicate which strategy is finally adopted with the rate distortion optimization, i.e., SRIP or traditional AIP. Extensive experimental results reveal that the proposed method can achieve 0.36% bit rate saving on average in case of lossless scenario.","PeriodicalId":431880,"journal":{"name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","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/VCIP49819.2020.9301752","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, a novel intra prediction method is presented for lossless/near lossless High Efficiency Video Coding (HEVC), termed as Sparse Representation based Intra Prediction (SRIP). In specific, the existing Angular Intra Prediction (AIP) modes in HEVC are organized as a mode dictionary, which is utilized to sparsely represent the visual signal by minimizing the difference with respect to the ground truth. For the match of encoding and decoding, the sparse coefficients are also required to be encoded and transmitted to the decoder side. To further improve the coding performance, an additional binary flag is included in the video codec to indicate which strategy is finally adopted with the rate distortion optimization, i.e., SRIP or traditional AIP. Extensive experimental results reveal that the proposed method can achieve 0.36% bit rate saving on average in case of lossless scenario.
本文提出了一种新的用于无损/近无损高效视频编码(HEVC)的帧内预测方法——基于稀疏表示的帧内预测(SRIP)。具体来说,HEVC中现有的Angular Intra Prediction (AIP)模式被组织成一个模式字典,通过最小化相对于ground truth的差异来稀疏表示视觉信号。为了编码和解码的匹配,还需要对稀疏系数进行编码并传输到解码器侧。为了进一步提高编码性能,在视频编解码器中加入一个额外的二进制标志来表示最终采用哪种策略进行速率失真优化,即SRIP还是传统的AIP。大量的实验结果表明,在无损情况下,该方法可以平均节省0.36%的比特率。