A Method for Extracting Area Water Body from Remote Sensing Images Using Active Contour Model and Vector Data
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摘要: 以矢量数据作为主动轮廓模型的初始位置,提出一种用于提取面状水体的新主动轮廓模型。在传统内部能量和外部能量的基础上加入基于目标-背景灰度的图像引力势能和基于离散曲率的形状约束势能,提高了模型的收敛速度和抗噪性能。充分利用矢量数据的先验信息,自适应地确定模型中的相关参数。同时,建立了基于相似性度量的提取精度评估模型,给出了基于贪婪算法的模型求解过程。最后,实验验证了本文方法的可行性与优越性。Abstract: Using vector data as the initial location of the model, the paper presents a new active contour model which is used to extracting area water body from remote sensing images. In order to improve constringency speed and noise immunity, the image gravitation potential energy based on object-background gray value is added to the new model besides the traditional energy. In order to avoid the noise on the curve point of attraction and disturbance, the shape restriction potential energy based on discrete curvature is also utilized in the new model. The correlative parameters are obtained adaptively by taking full use of prior information of vector data. The paper also establishes the precision evaluating model based on similarity measurement, and introduces the process of solving based on greedy algorithm. The experiment demonstrates the superiority of the method.
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