基于 GVF 和 Snake 模型的高分辨率遥感图像四元数空间道路提取

基于Snake模型的优势及缺陷，提出一种高分辨率多光谱图像道路提取方法。通过建立多光谱图像信息的四元数表达式，解决Snake模型应用于多光谱图像的局限性；通过多光谱图像四元数空间标记分水岭分割，获取道路初始轮廓，解决道路初始边界设置问题；通过梯度矢量流模型迭代求解，解决道路凹陷位置逼近问题，最终实现道路提取。用QuickBird 高分辨率多光谱遥感数据验证方法的可行性，与直接采用Snake 模型进行道路提取结果相比，本文所提出的方法对于高分辨率影像上的高等级道路提取具有较好的精度。

Road extraction in quaternion space from high spatial resolution remotely sensed images basing on GVF Snake model

A method of road extraction for high spatial resolution multi-spectral images is presented based on the advantages and disadvantages of Snake model theory. The quaternion expression of multi-spectral image is used to solve the limitation of Snake model for multi-spectral images. The road initial profi le is gotten by marked watershed segmentation in quaternion space with multi-spectral images which solve the question of how to set the initial border in the model. At the same time, how to get the approximate road hollow position is solved to realize the road contour extraction by gradient vector fl ow model with iterative solution. After experiments on QuickBird multi-spectral image with above method, the results indicate that the presented method is feasible for road extraction from high spatial resolution remote sensing image. Comparing with road extraction result by Snake model directly, the method presented in the paper has a better performance in extracting the main road contour information from high spatial resolution multi-spectral images.