视线(Line of Sight,LOS)计算在GIS、旅游,电信等很多领域里有着广泛的应用。在描述LOS计算方法的基础上提出了表征分辨率对LOS计算影响的因子los-eff,模拟了五种典型地貌特征的地形在降低分辨率时los-eff的变化情况。实验表明降低分辨...视线(Line of Sight,LOS)计算在GIS、旅游,电信等很多领域里有着广泛的应用。在描述LOS计算方法的基础上提出了表征分辨率对LOS计算影响的因子los-eff,模拟了五种典型地貌特征的地形在降低分辨率时los-eff的变化情况。实验表明降低分辨率可以使LOS计算时间近似指数下降,而在计算准确性方面,地貌特征简单的平原地形在降低分辨率后误差大于地貌特征复杂的山地地形,并且误差会随观察点高度增加而快速增加。因此可以根据不同的计算精度需要选择不同分辨率的DEM数据来进行视线计算,从而达到平衡计算时间和准确度的目的。展开更多
Current multi-operator image resizing methods succeed in generating impressive results by using image similarity measure to guide the resizing process. An optimal operation path is found in the resizing space. However...Current multi-operator image resizing methods succeed in generating impressive results by using image similarity measure to guide the resizing process. An optimal operation path is found in the resizing space. However, their slow resizing speed caused by inefficient computation strategy of the bidirectional patch matching becomes a drawback in practical use. In this paper, we present a novel method to address this problem. By combining seam carving with scaling and cropping, our method can realize content-aware image resizing very fast. We define cost functions combing image energy and dominant color descriptor for all the operators to evaluate the damage to both local image content and global visual effect. Therefore our algorithm can automatically find an optimal sequence of operations to resize the image by using dynamic programming or greedy algorithm. We also extend our algorithm to indirect image resizing which can protect the aspect ratio of the dominant object in an image.展开更多
文摘视线(Line of Sight,LOS)计算在GIS、旅游,电信等很多领域里有着广泛的应用。在描述LOS计算方法的基础上提出了表征分辨率对LOS计算影响的因子los-eff,模拟了五种典型地貌特征的地形在降低分辨率时los-eff的变化情况。实验表明降低分辨率可以使LOS计算时间近似指数下降,而在计算准确性方面,地貌特征简单的平原地形在降低分辨率后误差大于地貌特征复杂的山地地形,并且误差会随观察点高度增加而快速增加。因此可以根据不同的计算精度需要选择不同分辨率的DEM数据来进行视线计算,从而达到平衡计算时间和准确度的目的。
基金supported by the National Natural Science Foundation of China (NSFC) under Grant Nos. 60872120, 60902078, 61172104the Natural Science Foundation of Beijing under Grant No. 4112061+2 种基金the Scientific Research Foundation for the Returned Overseas Chinese Scholars of State Education Ministry of Chinathe French System@tic Paris-Region (CSDL Project)the National Agency for Research of French (ANR)-NSFC under Grant No. 60911130368
文摘Current multi-operator image resizing methods succeed in generating impressive results by using image similarity measure to guide the resizing process. An optimal operation path is found in the resizing space. However, their slow resizing speed caused by inefficient computation strategy of the bidirectional patch matching becomes a drawback in practical use. In this paper, we present a novel method to address this problem. By combining seam carving with scaling and cropping, our method can realize content-aware image resizing very fast. We define cost functions combing image energy and dominant color descriptor for all the operators to evaluate the damage to both local image content and global visual effect. Therefore our algorithm can automatically find an optimal sequence of operations to resize the image by using dynamic programming or greedy algorithm. We also extend our algorithm to indirect image resizing which can protect the aspect ratio of the dominant object in an image.
