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结合区域生长和GVF-Snake的遥感影像道路提取 被引量:3

Road extraction in remote sensing images based on region growing and GVF-Snake
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摘要 基于待分割目标的灰度特征分布,提出了一种能自适应地改变生长准则参数的区域生长方法。将该自适应区域生长算法与GVF-Snake模型相结合用于高分辨率遥感影像道路提取,即用自适应区域生长方法提取出大致的道路区域,对生长出的道路图,利用数学形态学进行内部腐蚀并获得道路区域轮廓线,以该轮廓线作为GVF-Snake模型的初始轮廓,利用GVF-Snake模型进行道路跟踪,得到最终的道路提取结果。实验结果表明该方法能有效地提取高分辨率遥感影像中的道路目标,具有一定的实用性和鲁棒性。 Based on the gray characteristic distribution of the objective to be segmented, an adaptive region growing algo-rithm is proposed, which can estimate the parameters of homogeneity criterion automatically.And the region growing algo- rithm with the GVF(Gradient Vector Flow)-snake model is employed to extract roads from high-resolution remote sensing images.In the method, the adaptive region growing algorithm is firstly applied to the preliminary road segmentation,and then mathematical morphology is utilized to eliminate disturbances inside and get the outline of the road in the grown image.Fi- nally, it uses the outline as the initial contour of the GVF-snake model, and applies the model to tracking the road, achiev- ing the final result of the road extraction.Experimental results show that the method is efficient and practical for extracting roads from high-resolution remote sensing images,and has a certain adaptive ability.
出处 《计算机工程与应用》 CSCD 北大核心 2010年第31期202-205,共4页 Computer Engineering and Applications
基金 国家自然科学基金No.40671133~~
关键词 自适应区域生长 GVF-Snake模型 高分辨率遥感影像 道路提取 adaptive region growing GVF-snake model high-resolution remote sensing images road extraction
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