Guang Y. Zhang, Abdelrahman Abdelazim, S. Mein, M. Varley, D. Ait-Boudaoud
{"title":"Inter-view Reference Frame Selection in Multi-view Video Coding","authors":"Guang Y. Zhang, Abdelrahman Abdelazim, S. Mein, M. Varley, D. Ait-Boudaoud","doi":"10.1109/DCC.2013.113","DOIUrl":null,"url":null,"abstract":"Summary form only given. Multiple video cameras are used to capture the same scene simultaneously to acquire the multiview view coding data, obviously, over-large data will affect the coding efficiency. Due to the video data is acquired from the same scene, the inter-view similarities between adjacent camera views are exploited for efficient compression. Generally, the same objects with different viewpoints are shown on adjacent views. On the other hand, containing objects at different depth planes, and therefore perfect correlation over the entire image area will never occur. Additionally, the scene complexity and the differences in brightness and color between the video of the individual cameras will also affect the current block to find its best match in the inter-view reference picture. Consequently, the temporal-view reference picture is referred more frequently. In order to gain the compression efficiency, it is a core part to disable the unnecessary inter-view reference. The idea of this paper is to exploit the phase correlation to estimate the dependencies between the inter-view reference and the current picture. If the two frames with low correlation, the inter-view reference frame will be disabled. In addition, this approach works only on non-anchor pictures. Experimental results show that the proposed algorithm can save 16% computational complexity on average, with negligible loss of quality and bit rate. The phase correlation process only takes up 0.1% of the whole process.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2013.113","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
Summary form only given. Multiple video cameras are used to capture the same scene simultaneously to acquire the multiview view coding data, obviously, over-large data will affect the coding efficiency. Due to the video data is acquired from the same scene, the inter-view similarities between adjacent camera views are exploited for efficient compression. Generally, the same objects with different viewpoints are shown on adjacent views. On the other hand, containing objects at different depth planes, and therefore perfect correlation over the entire image area will never occur. Additionally, the scene complexity and the differences in brightness and color between the video of the individual cameras will also affect the current block to find its best match in the inter-view reference picture. Consequently, the temporal-view reference picture is referred more frequently. In order to gain the compression efficiency, it is a core part to disable the unnecessary inter-view reference. The idea of this paper is to exploit the phase correlation to estimate the dependencies between the inter-view reference and the current picture. If the two frames with low correlation, the inter-view reference frame will be disabled. In addition, this approach works only on non-anchor pictures. Experimental results show that the proposed algorithm can save 16% computational complexity on average, with negligible loss of quality and bit rate. The phase correlation process only takes up 0.1% of the whole process.