针对有复杂场景的城市航拍图像,提出了一种基于D-S证据理论的道路提取方法.首先建立道路模型;然后将图像分块,建立灰度连通集,并选取子图像中较大的灰度连通集作为候选道路段;根据道路模型从候选道路段中提取特征来定义多个概率分配函数BPAF(basic probability assignment functions),并使用Dempster合成法则对其进行合成,识别出道路段;最后将已识别出的道路段进行合并,排除错误路段,形成道路.实验结果证明了这一方法的有效性.
An approach is presented to extract roads from aerial city images based on the Dempster-Shafer evidence theory. A road model is a priori constructed. Aerial images are divided into sub-blocks from which regions consisting of 8-connected pixels with similar gray scales are obtained, and regions with relatively big areas are selected as candidate road segments. Then Dempster rule is applied to compute the fusion of basic probability assignment functions (BPAF) defined respectively on the features extracted from the candidate road segments and on the original road model. Finally, the BPAF fusion is utilized to find the conclusive road segments and these road segments are connected and pruned to form the de facto roads. Experimental results demonstrate the ability of the D-S evidence theory based approach to accurately extract roads from aerial city images.
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