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浙江大学学报(工学版)
J4  2013, Vol. 47 Issue (4): 581-587    DOI: 10.3785/j.issn.1008-973X.2013.04.003
    
Multi-level method of optimizing vector graphs converted from remote sensing images
WU Ning1, CHEN Qiu-xiao2, ZHOU Ling2, WAN Li2
1.Department of Architecture, Zhejiang University, Hangzhou 310058, China|
2. Department of Regional andUrban Planning, Zhejiang University, Hangzhou 310058, China
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Abstract  

A multi-level optimization method for vector graphs converted from remote sensing images was proposed. The smoothing operation was implemented on curves with collinear nodes included in order to reduce the errors generated by the discretization of raster data. The single-level compression operation was implemented to remove most of the redundant nodes which have less effect on the shape of curves. The adaptive multi-level compression operation was executed to make all kinds of curves be close to the real boundaries as much as possible. A large number of comparative experiments were conducted in the aspects of adaptability both to segmentation scale and spatial resolution, using diversities of vector graphs. Results proved the effectiveness and robustness of the method.

Published: 01 April 2013
CLC:  TP 391  
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Cite this article:

WU Ning, CHEN Qiu-xiao, ZHOU Ling, WAN Li. Multi-level method of optimizing vector graphs converted from remote sensing images. J4, 2013, 47(4): 581-587.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2013.04.003     OR     http://www.zjujournals.com/eng/Y2013/V47/I4/581


遥感影像矢量化图形的多层次优化方法

提出针对遥感影像矢量化图形的多层次优化方法.该方法对边界进行纳入共线点的平滑处理,以此削弱由栅格数据离散化造成的误差；通过单层次的压缩以去除大部分对形状影响不大的冗余节点；执行自适应多层次的压缩,从而使各类地物的边界最大限度地逼近真实轮廓.以多幅图形为例,从对影像分割尺度的适应性、空间分辨率的适应性2方面与传统方法作了大量对比实验,证明了该方法的有效性和鲁棒性.

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