Studies on parallel and distributed RS image issuance system based on SVM
文献类型：会议论文
| 作者 | Wu H. Q. ; Chi T. H. ; Fang J. Y. ; Zhang X. ; Ieee |
| 出版日期 | 2003 |
| 关键词 | multi-sensor RS image data parllel computer clusters SVM (sharing virtual memory) solid index mechanism |
| 页码 | 3790-3792 |
| 英文摘要 | Remote sensing data has the property of large volume data, multi-sensor, multi-resolution, multi-spectrum and multiepoch, which bring forth some difficulties for RS image's Geo-Information sharing and issuance. The following are two prominent difficulties: Firstly, background severs need to handle heavy process of data. Secondly, there is no efficient organization of RS image data for storage and management on the background. Aiming at above status, this paper has studied adopting parallel computers based on SVM as background servers for RS image's distributed issuance system, and analyzed parallel procedure design for image data based on the parallel computer clusters. Furthermore this paper has analyzed and tested the parallel process of image extracting, image matching and image compressing of the background. Test results have indicated that these parallel computers could promote the background performance distinctly. As for the organization of image data, this paper has constructed a solid index mechanism of 'Pyramid, Block, Layer, Epoch" according to the properties of RS data and established a corresponding logic database for it. RS data still distribute on parallel computers in files, not in database as blobs. All server side processes are performed through the logic database. According to the above ideas, this paper has designed the issuance system, which provides storage, management, query and browse of RS image data at a distributed environment. |
| 收录类别 | CPCI |
| 会议录出版者 | Ieee |
| 语种 | 英语 |
| ISBN号 | 0-7803-7929-2 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/25322]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Wu H. Q.,Chi T. H.,Fang J. Y.,et al. Studies on parallel and distributed RS image issuance system based on SVM[C]. 见:. |
入库方式： OAI收割
来源：地理科学与资源研究所
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