数学形态法在超宽带SAR 道路边缘检测中的应用

超宽带SAR由于杂波模型多样化，当使用传统的基于单一杂波统计模型进行边缘检测时容易造成虚警高，定位精度差，边缘不连续，处理时间长等问题。基于数学形态学思想, 提出了一种多方向多尺度结构元素的二值形态学边缘检测算法，先对原始图像进行二值化处理，再运用多方向多尺度结构元素进行循环闭-开形态运算得到多个方向结果图，最后将各方向结果图进行融合得到最终的图像边缘。与传统边缘检测算法的对比实验表明,本文提出的算法由于采用了多尺度结构元素并且结合了图像的灰度信息，图像边缘检测虚警低，定位精确，耗时短，边缘更连续。

The application of morphology to the edge detection of road from UWB SAR images

Due to the multifomity of the clutter statistic property in UWB SAR image, there are much false lines, discontinuity of road edge and big computation load when using traditional method based on one clutter statistical property, like ROA, to detect road edge from UWB SAR image. In this article, a novel method based on morphology is proposed which not only uses multidirectional and multiscale structures, but also utilizes original gray image information. First, the original image is transformed to binary image. Second, circular close-open operation is processed with the structures mentioned above to get consequential images. Finally with the original gray image information, the consequential images are fused to obtain the final results. Experiments show that the presented method, compared with the traditional edge detecting methods, can get fewer false lines, more accurate localization, better continuity and smaller computational load.