{"title":"Wavelet Decomposition Pre-processing for Spatial Scalability Video Compression Scheme","authors":"Glenn Herrou, W. Hamidouche, L. Morin","doi":"10.1109/PCS.2018.8456307","DOIUrl":null,"url":null,"abstract":"Scalable video coding enables to compress the video at different formats within a single layered bitstream. SHVC, the scalable extension of the High Efficiency Video Coding (HEVC) standard, enables x2 spatial scalability, among other additional features. The closed-loop architecture of the SHVC codec is based on the use of multiple instances of the HEVC codec to encode the video layers, which considerably increases the encoding complexity. With the arrival of new immersive video formats, like 4K, 8K, High Frame Rate (HFR) and 360° videos, the quantity of data to compress is exploding, making the use of high-complexity coding algorithms unsuitable. In this paper, we propose a lowcomplexity scalable coding scheme based on the use of a single HEVC codec instance and a wavelet-based decomposition as pre-processing. The pre-encoding image decomposition relies on well-known simple Discrete Wavelet Transform (DWT) kernels, such as Haar or Le Gall 5/3. Compared to SHVC, the proposed architecture achieves a similar rate distortion performance with a coding complexity reduction of 50%.","PeriodicalId":433667,"journal":{"name":"2018 Picture Coding Symposium (PCS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Picture Coding Symposium (PCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCS.2018.8456307","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
Scalable video coding enables to compress the video at different formats within a single layered bitstream. SHVC, the scalable extension of the High Efficiency Video Coding (HEVC) standard, enables x2 spatial scalability, among other additional features. The closed-loop architecture of the SHVC codec is based on the use of multiple instances of the HEVC codec to encode the video layers, which considerably increases the encoding complexity. With the arrival of new immersive video formats, like 4K, 8K, High Frame Rate (HFR) and 360° videos, the quantity of data to compress is exploding, making the use of high-complexity coding algorithms unsuitable. In this paper, we propose a lowcomplexity scalable coding scheme based on the use of a single HEVC codec instance and a wavelet-based decomposition as pre-processing. The pre-encoding image decomposition relies on well-known simple Discrete Wavelet Transform (DWT) kernels, such as Haar or Le Gall 5/3. Compared to SHVC, the proposed architecture achieves a similar rate distortion performance with a coding complexity reduction of 50%.
可扩展的视频编码可以在单个层比特流中压缩不同格式的视频。SHVC是高效视频编码(HEVC)标准的可扩展扩展,支持x2空间可扩展性,以及其他附加功能。SHVC编解码器的闭环架构是基于使用多个HEVC编解码器实例对视频层进行编码,这大大增加了编码复杂度。随着新的沉浸式视频格式的出现,如4K、8K、高帧率(HFR)和360°视频,需要压缩的数据量呈爆炸式增长,这使得使用高复杂性的编码算法变得不合适。在本文中,我们提出了一种基于单个HEVC编解码器实例和基于小波分解作为预处理的低复杂度可扩展编码方案。预编码图像分解依赖于众所周知的简单离散小波变换(DWT)核,如Haar或Le Gall 5/3。与SHVC相比,该结构在编码复杂度降低50%的情况下实现了相似的率失真性能。