【作者】 肖晓柏； 李培军；

【Author】 XIAO Xiao bai, LI Pei jun ( Institute of Remote Sensing and Geographic Information System, Peking University , Beijing 100871, China)

【机构】 北京大学遥感与地理信息系统研究所；

【摘要】 从遥感图像特别是高分辨率遥感图像上提取线性特征是当前的研究热点。尝试用方向性形态变换的方法来提取线性特征。采用白Top hat变换,并运用多个角度(0°,45°,90°,135°)和不同长度的线段结构元素,对韩国KOMPSAT EOC高分辨率全色(6.6 m分辨率)影像进行线性特征提取,探讨了结构元素的原点位置、角度、和尺寸等对变换结果的影响。结果表明:(1)采用白Top hat变换能够显著地增强线性特征而压制其它非线性特征,是一种非常有效的增强和提取图像线性特征的方法;(2)采用特定角度的线段结构元素能够提取与之垂直角度的线性特征;(3)随着线段结构元素长度增大,连续性变好,但与结构元素同角度的噪声也会随之增加,因此最佳的线段结构元素长度的确定应同时考虑增强线性特征和减少噪声两方面的因素。更多还原

【Abstract】 The extraction of lineaments from remote sensing images is a major focus of remote sensing research fields. In this paper, the directional morphological transformation method is used to extract the lineaments. The white top hat transformation and the structuring elements with line segments of 4 directions (N, NE, E and SE) and different lengths were used to extract lineaments from remote sensing images,and the effects of origin location, direction and size of structurng element on the transformed results were discussed. It is shown from the transformed results that (1) the white top hat transformation can greatly enhance the lineaments and suppress non lineaments in the images, so the transformation is an effective method for enhancing and extracting the lineaments from images; (2) the use of structuring element of specific direction can enhance and extract the lineaments perpendicular to the structuring element; (3) the continuity of the extracted lineaments was improved with increasing length of structuring element, but the noise along the direction of structuring element also increased, so both the enhancement of lineaments and the reduction of noise should be considered in determining the optimal length of structuring element.更多还原