R. Kozhemiakin, S. Abramov, V. Badenko, Blazo Djurovic, I. Djurović, B. Vozel
{"title":"陆地卫星多光谱图像的有损压缩","authors":"R. Kozhemiakin, S. Abramov, V. Badenko, Blazo Djurovic, I. Djurović, B. Vozel","doi":"10.1109/MECO.2016.7525714","DOIUrl":null,"url":null,"abstract":"We consider practical aspects of lossy compression with application to multispectral images provided by Landsat sensor. Two facts are taken into account: 1) the inherent noise presence and its properties; 2) rather high degree of component correlation. These properties in different degree are used in 2D and 3D lossy compression. Comparison of the suggested approaches has been carried out for some compression ratios. It is demonstrated that 3D-compression using techniques based on discrete cosine transform (DCT) can provide some benefits but only under condition of proper grouping of sub-band images.","PeriodicalId":253666,"journal":{"name":"2016 5th Mediterranean Conference on Embedded Computing (MECO)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Lossy compression of Landsat multispectral images\",\"authors\":\"R. Kozhemiakin, S. Abramov, V. Badenko, Blazo Djurovic, I. Djurović, B. Vozel\",\"doi\":\"10.1109/MECO.2016.7525714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider practical aspects of lossy compression with application to multispectral images provided by Landsat sensor. Two facts are taken into account: 1) the inherent noise presence and its properties; 2) rather high degree of component correlation. These properties in different degree are used in 2D and 3D lossy compression. Comparison of the suggested approaches has been carried out for some compression ratios. It is demonstrated that 3D-compression using techniques based on discrete cosine transform (DCT) can provide some benefits but only under condition of proper grouping of sub-band images.\",\"PeriodicalId\":253666,\"journal\":{\"name\":\"2016 5th Mediterranean Conference on Embedded Computing (MECO)\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 5th Mediterranean Conference on Embedded Computing (MECO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MECO.2016.7525714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 5th Mediterranean Conference on Embedded Computing (MECO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MECO.2016.7525714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We consider practical aspects of lossy compression with application to multispectral images provided by Landsat sensor. Two facts are taken into account: 1) the inherent noise presence and its properties; 2) rather high degree of component correlation. These properties in different degree are used in 2D and 3D lossy compression. Comparison of the suggested approaches has been carried out for some compression ratios. It is demonstrated that 3D-compression using techniques based on discrete cosine transform (DCT) can provide some benefits but only under condition of proper grouping of sub-band images.
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