摘要
【目的】视觉平衡是影响地图信息传输效率和视觉美感的重要因素之一。尽管现有的视觉平衡度计算方法在传统地图的度量和评价方面表现出色,但面对个性化要素配置的微地图时,其适用性却大打折扣。尤为突出的是,微地图图面要素的活跃性导致其分布格局复杂且量化工作艰巨,给微地图的视觉平衡度计算造成了极大挑战。【方法】本文提出了一种多因子驱动的微地图视觉平衡度计算方法。首先对每幅微地图进行自适应共现滤波和隶属度矩阵划分,以优化图像分布特征,确定各要素的归属程度,实现基于鲁棒模糊C均值聚类的图面配置要素提取。接着引入亮度、对比度、显著性3个视觉特征因子,分别关注图像的重量、细节和焦点,量化图面要素布局的配置权重。最后,依据图面要素视觉重心与几何中心的距离及方位构建微地图视觉平衡度计算方法。依据上述方法,构建了一个涵盖项目原创、新闻媒体及旅游官网等多种数据源的78幅微地图实验数据集,并通过参数影响实验、评价调查与对比实验、图面要素分布变化实验等,依次验证所提方法的有效性。【结果】当距离权重α为0.8,角度权重β为0.2时,提出的视觉平衡度计算方法最符合人类的审美认知。【结论】所提方法与专家制图经验高度契合,体现了良好的人类视觉认知模拟性能。
[Objectives]Visual balance is one of the most important factors affecting the efficiency of map information communication and visual aesthetics.Although existing balance calculation methods are effective for traditional maps,their applicability is significantly reduced when applied to WeMaps with personalized element configurations.The dynamic nature of elements on WeMaps leads to complex distribution patterns and challenging quantification,posing a major obstacle to visual balance calculation for WeMaps.[Methods]To address this issue,a multifactor-driven method for calculating the visual balance of WeMaps is proposed.First,adaptive co-occurrence filtering and affiliation matrix partitioning are applied to each WeMap to optimize image distribution features and determine the degree of attribution for each element.This enables the extraction of map layout elements based on robust fuzzy C-means clustering.Next,three visual perception factors,brightness,contrast,and saliency,are introduced to quantify the visual weight,detail,and focus of graphical elements,respectively.Finally,using the Euclidean distance and angle between the visual center of gravity and the visual center of the graphical elements,a model for calculating the visual balance of WeMaps is constructed.An experimental dataset of 78 WeMaps was built using data from project designs,news sources,and official tourism websites.The effectiveness of the proposed method was validated through six parameter adjustment experiments,evaluation surveys,comparative experiments,and visual feature variation tests.[Results]The experimental results show that when the distance weightαis set to 0.8 and the angled weightβto 0.2,the proposed method aligns best with human aesthetic perception.[Conclusions]The proposed method is highly consistent with expert cartographic experience and effectively simulates human visual cognition,demonstrating strong practical applicability.
作者
马荣娟
闫浩文
禄小敏
李精忠
侯昭阳
李蓬勃
毛富康
MA Rongjuan;YAN Haowen;LU Xiaomin;LI Jingzhong;HOU Zhaoyang;LI Pengbo;MAO Fukang(Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070,China;National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring,Lanzhou 730070,China;Gansu Provincial Key Laboratory of Science and Technology in Surveying&Mapping,Lanzhou 730070,China)
出处
《地球信息科学学报》
北大核心
2025年第7期1551-1565,共15页
Journal of Geo-information Science
基金
国家自然科学基金项目(42430108、42161066、42471476)。
关键词
微地图
视觉平衡
模糊聚类
视觉重心
自适应共现滤波
隶属度矩阵划分
WeMap
visual balance
fuzzy clustering
visual center of gravity
adaptive co-occurrence filtering
affiliation matrix division
