›› 2013, Vol. 42 ›› Issue (5): 767-773.

• 学术论文 • 上一篇    下一篇

基于层次信息量的线要素化简算法性能评价研究

邓敏1,樊子德2,刘慧敏2   

  1. 1. 中南大学
    2. 中南大学地球科学与信息物理学院
  • 收稿日期:2012-09-17 修回日期:2013-01-14 出版日期:2013-10-20 发布日期:2014-01-23
  • 通讯作者: 邓敏 E-mail:dengmin028@yahoo.com
  • 基金资助:
    国家自然科学基金项目

Performance Evaluation of Line Simplification Algorithms Based on Hierarchical Information Content

  • Received:2012-09-17 Revised:2013-01-14 Online:2013-10-20 Published:2014-01-23

摘要: 化简算法是地图综合的一类基本算法,而算法性能评价是解决算法优化和算法选取的一个重要问题。现有评价指标更多地考虑要素化简前后的位置偏移,难以客观地评价算法性能。为此,本文以线要素为例,全面考虑线要素化简原则,从信息传递的角度,提出一种基于层次信息量的线要素化简算法性能评价方法。首先将线要素的信息划分为三个层次来描述,即:元素层次、邻域层次和整体层次,并发展相应的信息量计算方法。然后,从化简后各层次信息量的保持能力(或信息传递能力)来评价线要素化简算法的性能。其中,元素层次信息传递比评价关键点保持性能;邻域层次信息传递比评价弯曲保持性能;整体层次信息传递比评价整体形态保持性能。最后,以河网为例,采用层次信息量指标,对四种经典化简算法进行评价,分析验证了层次信息量评价指标的合理性,与经典评价指标的对比分析进一步验证了该指标的优越性。

关键词: 性能评价, 层次性, 信息量, 线要素化简, 地图综合

Abstract: Simplification has always been a commonly-used generalization operator, and a number of simplification algorithms are currently available. It is natural to further pay more attention to the performance evaluation of these algorithms. With regard to this, there are some representative evaluation indicators which are proposed with the consideration of the differences of the location and/or shape of spatial features. Indeed, these individual indicators only consider some aspect of the distortions caused by generalization, so that it is difficult to comprehensively reflect the performance of simplification algorithms. To overcome such problem, this paper takes line feature as an example and develops a new evaluation indicator (i.e. information content) at three levels (i.e. element, neighborhood and holistic levels) from the view of information transmission. The process of performance evaluation mainly involves the calculation and the comparison of information content before and after line simplification. As for the former, the quantitative computational methods of information content at the three levels are presented. As for the latter, the difference of information content before and after line simplification is computed and utilized to measure performance of line simplification algorithms. The difference degree of information content at element level reflects the ability of line simplification algorithms to select key points; the difference degree of information content at neighborhood level reflects the ability of line simplification algorithms to maintain bends; the difference degree of information content at holistic level reflects the ability of line simplification algorithm to maintain the trend of line features. Finally, a river network dataset is used to test the performance evaluations of four common-used line simplification algorithms according to the proposed indicator of information content. It is proven that this new indicator is very rational to evaluate the performance of these four line simplification algorithms. At the meantime, a comparative test is made to show the advantages of the new evaluation indicator.

Key words: performance evaluation, hierarchy, information content, line simplification, map generalization

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