| 基于簇模型的矢量地图数据的高效压缩方法(英文) |
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| 引用本文： | 杨必胜,李清泉.基于簇模型的矢量地图数据的高效压缩方法(英文)[J].地球空间信息科学学报,2009,12(1):13-17. |
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| 作者姓名： | 杨必胜 李清泉 |
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| 作者单位： | State;Laboratory;Information;Engineering;Surveying;Mapping;Remote;Sensing;Wuhan;University; |
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| 基金项目： | Supported by the National 863 Program of China (No. 2007AAl2Z241);;the Program for New Century Excellent Talents in University (No. NCET-07-0643);;the National Natural Science Foundation of China (No. 40571134,No. 40871185);;the National 973 Program of China (No. 108085) |
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| 摘 要： |
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| 关 键 词： | 地图数据 高效 矢量 压缩方法 簇模型 |
Efficient compression of vector data map based on a clustering model |
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| Bisheng Yang,Qingquan Li.Efficient compression of vector data map based on a clustering model[J].Geo-Spatial Information Science,2009,12(1):13-17. |
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| Authors: | Bisheng Yang Qingquan Li |
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| Institution: | (1) State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China |
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| Abstract: | This paper proposes a new method for the compression of vector data map. Three key steps are encompassed in the proposed method,
namely, the simplification of vector data map via the elimination of vertices, the compression of removed vertices based on
a clustering model, and the decoding of the compressed vector data map. The proposed compression method was implemented and
applied to compress vector data map to investigate its performance in terms of the compression ratio and distortions of geometric
shapes. The results show that the proposed method provides a feasible and efficient solution for the compression of vector
data map and is able to achieve a promising ratio of compression and maintain the main shape characteristics of the spatial
objects within the compressed vector data map.
Supported by the National 863 Program of China (No. 2007AAl2Z241), the Program for New Century Excellent Talents in University
(No. NCET-07-0643), the National Natural Science Foundation of China (No. 40571134, No. 40871185), the National 973 Program
of China (No. 108085). |
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| Keywords: | spatial data decoding spatial data compression error evaluation |
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