{"title":"基于奇异值分解的多尺度DEM生成","authors":"Caixian Zhang, Jun He, Wenguang Hou","doi":"10.1117/12.2537903","DOIUrl":null,"url":null,"abstract":"As the fundamental data about the terrains, DEM plays an important role in many fields. The high resolution DEM is increasingly popular. Yet, the multiscale resolution DEMs are still desired for some applications due to the fact that the low resolution DEM can reduce the memory demands with limited computational complexity. Then, how to obtain the multiscale DEMs remains an open question, which demands that the different resolution DEMs should discard the detailed information with maintaining the main information of the high resolution DEM. Moreover, the multiscale DEMs should not cost many memories. Generally, there is a contradiction. As such, this paper proposes a multiscale DEM generation method based on Singular Value Decomposition (SVD) which can establish multiscale DEMs maintaining the different details with a small quantity of memory increasement. The method is simple but effective. Lots of experiment shows its effectiveness.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multiscale DEM generation on basis of singular value decomposition\",\"authors\":\"Caixian Zhang, Jun He, Wenguang Hou\",\"doi\":\"10.1117/12.2537903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the fundamental data about the terrains, DEM plays an important role in many fields. The high resolution DEM is increasingly popular. Yet, the multiscale resolution DEMs are still desired for some applications due to the fact that the low resolution DEM can reduce the memory demands with limited computational complexity. Then, how to obtain the multiscale DEMs remains an open question, which demands that the different resolution DEMs should discard the detailed information with maintaining the main information of the high resolution DEM. Moreover, the multiscale DEMs should not cost many memories. Generally, there is a contradiction. As such, this paper proposes a multiscale DEM generation method based on Singular Value Decomposition (SVD) which can establish multiscale DEMs maintaining the different details with a small quantity of memory increasement. The method is simple but effective. Lots of experiment shows its effectiveness.\",\"PeriodicalId\":384253,\"journal\":{\"name\":\"International Symposium on Multispectral Image Processing and Pattern Recognition\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Multispectral Image Processing and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2537903\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Multispectral Image Processing and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2537903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiscale DEM generation on basis of singular value decomposition
As the fundamental data about the terrains, DEM plays an important role in many fields. The high resolution DEM is increasingly popular. Yet, the multiscale resolution DEMs are still desired for some applications due to the fact that the low resolution DEM can reduce the memory demands with limited computational complexity. Then, how to obtain the multiscale DEMs remains an open question, which demands that the different resolution DEMs should discard the detailed information with maintaining the main information of the high resolution DEM. Moreover, the multiscale DEMs should not cost many memories. Generally, there is a contradiction. As such, this paper proposes a multiscale DEM generation method based on Singular Value Decomposition (SVD) which can establish multiscale DEMs maintaining the different details with a small quantity of memory increasement. The method is simple but effective. Lots of experiment shows its effectiveness.