{"title":"Lossless Compression of Stereo Disparity Maps for 3D","authors":"M. Zamarin, Søren Forchhammer","doi":"10.1109/ICMEW.2012.113","DOIUrl":null,"url":null,"abstract":"Efficient compression of disparity data is important for accurate view synthesis purposes in multi-view communication systems based on the \"texture plus depth\" format, including the stereo case. In this paper a novel technique for loss less compression of stereo disparity images is presented. The coding algorithm is based on bit-plane coding, disparity prediction via disparity warping and context-based arithmetic coding exploiting predicted disparity data. Experimental results show that the proposed compression scheme achieves average compression factors of about 48:1 for high resolution disparity maps for stereo pairs and outperforms different standard solutions for loss less still image compression. Moreover, it provides a progressive representation of disparity data as well as a parallelizable structure.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Multimedia and Expo Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW.2012.113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Efficient compression of disparity data is important for accurate view synthesis purposes in multi-view communication systems based on the "texture plus depth" format, including the stereo case. In this paper a novel technique for loss less compression of stereo disparity images is presented. The coding algorithm is based on bit-plane coding, disparity prediction via disparity warping and context-based arithmetic coding exploiting predicted disparity data. Experimental results show that the proposed compression scheme achieves average compression factors of about 48:1 for high resolution disparity maps for stereo pairs and outperforms different standard solutions for loss less still image compression. Moreover, it provides a progressive representation of disparity data as well as a parallelizable structure.