基于总变分和形态学的航空图像道路检测算法

高分辨率航空图像中道路通常表现为较狭窄的面,这给分类算法创造了机会.文中提出了一种新的基于分类的航空图像道路自动提取方法--基于总变分和形态学分析方法,它首先根据邻域总变分和直方图得到分割道路所需的合适阈值并从图像中分割出道路区域,然后根据基于区域总变分和几何测度的准则函数及其模式频谱得到形态学普通开运算的阈值,最后用此准则及阈值对图像进行形态学普通开运算以去除和路面具有相似光谱特性的物体的干扰.初步实验证明,该方法具有良好的稳定性和较强的环境适应能力.

Road Extraction Algorithm for Aerial Images Based on Total Variations and Mathematical Morphology

Roads in high resolution aerial images appear to be narrow areas and this creates an opportunity for classification based methods. A new approach based on classification to road extraction for aerial images is proposed in this paper. The method is based on total variation and mathematical morphology analysis. This approach firstly classifies the image into road and non-road pixels by appropriate thresholds based on neighbor total variations and histogram analysis, and then uses a criterion based on connected area total variations, geometric attributes and its pattern spectrum to find an appropriate threshold for morphological trivial opening. Finally, morphological trivial opening is adopted to avoid noises including objects that have similar spectral characteristics to road surfaces. Strict experiments show that this algorithm is robust and is capable of coping with partial occlusion and extracting roads with different spectral characteristics in the same image.