【摘要】 合并变换是将匹配地物的不同表现形式一致化,它是地图合并过程中解决数据二义性问题的一个关键步骤。以往的解决方法都是依据一幅图对另一幅图进行直接调整,没有考虑另一幅图上要素的位置对合并变换的影响,这必定带来一定的误差。研究多评价因素的点状要素合并变换算法,分析确定影响合并变换的三大主要评价因素,并通过熵法决定其重要性,进而使用加权平均来获得合并变换后的位置。最后结合海陆图的部分点状要素对该算法加以检验,结果表明该算法提高了点状要素的空间位置合并变换质量。更多还原

【Abstract】 Adjusting is defined as making different representation of matching objects consistent.It is a key step to resolve data ambiguity in the process of map conflation.Previous methods adjust one map directly without considering the influence caused by the point features from the second map,which certainly brings some error.To solve this problem,the point feature adjusting algorithm based on multi-evaluation factors was studied.Three primary evaluation factors were analyzed,and their importance was given by the method of entropy,then the adjusted position was obtained with a weighted average algorithm.Finally some same point features from a sea chart and a topographic map were utilized to test the proposed algorithm.The result shows that it can improve the quality of point feature adjusting.更多还原