航空影像上线状地物的半自动提取

提出了一种顾及操作性、稳定性、精度和速度的从航空影象半自动撮线状地物的策略和算法。在人工依次输入的每两个初始点之间，提取连续的抛物线。该方法先通过二模板快速相关和优化计算得到剔除了错误匹配后的初始抛物线参数，然后以其为初值，基于整体最小二乘法模板匹配，解求参数的精确值，以获得更高的定位精度。通过自适应的模板克服了线特征的对比度和线宽度的变化对定位带来的影响。实验结果表明，该算法有较强的抗干扰能力和较高的精度，有较好的实用价值。

Semiautomatic Extraction of Linear Object form Aerial Image

The paper introduces a method of semiautomatic extraction of linear objects from aerial images that has good interactive performance, robustness, accuracy and real time response. A linear object is extracted as a consecutive parabola between each input two seed points. First, through fast binary template matching by correlation and optimize algorithm, the initial parameters of the parabola which have eliminated the blunders caused by shadow and other noises are calculated, and then the least squares template matching is used for accurate positioning by evaluating the adjusted precise parameters of the parabola. This paper specifies the mathematical model of least square template matching and the self adaptive template generation to overcome the effects of changes of the width and contrast of the linear feature. The least squares template matching could also be seen as an optimal algorithm that integrates the image feature and geometrical constraints together and has been studied well for long terms. If the proper initial values have been given, the least square method works well and is often applied to solve the accurate positioning problem. The experimental results indicate that the method could gain high accuracy and is robust and ready to practical mapping production from aerial images.