{"title":"使用基于层的表示的多视图图像压缩","authors":"Andriy Gelman, P. Dragotti, V. Velisavljevic","doi":"10.1109/ICIP.2010.5651160","DOIUrl":null,"url":null,"abstract":"We propose a novel compression method for multiview images. The algorithm exploits the layer-based representation, which partitions the data set into planar layers characterized by a constant depth value. For efficient compression, the partitioned data is decorrelated using the separable three-dimensional wavelet transform across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. The generated transform coefficients are entropy coded. Experimental results show that our coding method is capable of outperforming the state-of-the-art algorithms, like H.264/AVC, for different data sets.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Multiview image compression using a layer-based representation\",\"authors\":\"Andriy Gelman, P. Dragotti, V. Velisavljevic\",\"doi\":\"10.1109/ICIP.2010.5651160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel compression method for multiview images. The algorithm exploits the layer-based representation, which partitions the data set into planar layers characterized by a constant depth value. For efficient compression, the partitioned data is decorrelated using the separable three-dimensional wavelet transform across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. The generated transform coefficients are entropy coded. Experimental results show that our coding method is capable of outperforming the state-of-the-art algorithms, like H.264/AVC, for different data sets.\",\"PeriodicalId\":228308,\"journal\":{\"name\":\"2010 IEEE International Conference on Image Processing\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2010.5651160\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2010.5651160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiview image compression using a layer-based representation
We propose a novel compression method for multiview images. The algorithm exploits the layer-based representation, which partitions the data set into planar layers characterized by a constant depth value. For efficient compression, the partitioned data is decorrelated using the separable three-dimensional wavelet transform across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. The generated transform coefficients are entropy coded. Experimental results show that our coding method is capable of outperforming the state-of-the-art algorithms, like H.264/AVC, for different data sets.