Francesc Aulí Llinàs, Joan Bartrina-Rapesta, J. Serra-Sagristà, M. Marcellin
{"title":"低复杂度、高效率的高光谱图像编码概率模型","authors":"Francesc Aulí Llinàs, Joan Bartrina-Rapesta, J. Serra-Sagristà, M. Marcellin","doi":"10.1109/CCP.2011.10","DOIUrl":null,"url":null,"abstract":"This paper describes a low-complexity, high-efficiency lossy-to-lossless coding scheme for hyper-spectral images. Together with only a 2D wavelet transform on individual image components, the proposed scheme achieves coding performance similar to that achieved by a 3D transform strategy that adds one level of wavelet decomposition along the depth axis of the volume. The proposed schemes operates by means of a probability model for symbols emitted by the bit plane coding engine. This probability model captures the statistical behavior of hyper-spectral images with high precision. The proposed method is implemented in the core coding system of JPEG2000 reducing computational costs by 25%.","PeriodicalId":167131,"journal":{"name":"2011 First International Conference on Data Compression, Communications and Processing","volume":"149 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Low Complexity, High Efficiency Probability Model for Hyper-spectral Image Coding\",\"authors\":\"Francesc Aulí Llinàs, Joan Bartrina-Rapesta, J. Serra-Sagristà, M. Marcellin\",\"doi\":\"10.1109/CCP.2011.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a low-complexity, high-efficiency lossy-to-lossless coding scheme for hyper-spectral images. Together with only a 2D wavelet transform on individual image components, the proposed scheme achieves coding performance similar to that achieved by a 3D transform strategy that adds one level of wavelet decomposition along the depth axis of the volume. The proposed schemes operates by means of a probability model for symbols emitted by the bit plane coding engine. This probability model captures the statistical behavior of hyper-spectral images with high precision. The proposed method is implemented in the core coding system of JPEG2000 reducing computational costs by 25%.\",\"PeriodicalId\":167131,\"journal\":{\"name\":\"2011 First International Conference on Data Compression, Communications and Processing\",\"volume\":\"149 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 First International Conference on Data Compression, Communications and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCP.2011.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 First International Conference on Data Compression, Communications and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCP.2011.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low Complexity, High Efficiency Probability Model for Hyper-spectral Image Coding
This paper describes a low-complexity, high-efficiency lossy-to-lossless coding scheme for hyper-spectral images. Together with only a 2D wavelet transform on individual image components, the proposed scheme achieves coding performance similar to that achieved by a 3D transform strategy that adds one level of wavelet decomposition along the depth axis of the volume. The proposed schemes operates by means of a probability model for symbols emitted by the bit plane coding engine. This probability model captures the statistical behavior of hyper-spectral images with high precision. The proposed method is implemented in the core coding system of JPEG2000 reducing computational costs by 25%.