一种用细胞神经网提取遥感图像边缘的新方法*

针对灰度遥感图像具有噪声多、图像亮度均匀、边缘模糊等特点，提出了基于细胞神经网遥感图像边缘检测的新方法。该算法主要是利用细胞神经网先后对遥感图像进行图像滤波、灰度阈值化、膨胀腐蚀、边缘检测等模板操作。实验结果表明，与传统的Sobel和Canny边缘检测算法相比，本算法不仅能有效地去除噪声对边缘检测的影响，而且能够快速完整地提取图像边缘。

Novel CNN algorithm for extracting remote sensing image edge

As gray remote sensing image had the characteristics of much noise, image brightness uniformity, and fuzzy edge, a novel edge detection method based on cellular neural networks (CNN)was presented. In the algorithm, image filtering, gray threshold segmentation, dilation and erosion, and edge detection using CNN were performed for remote sensing image successively. The experimental results show that the proposed algorithm,compared with the triditional edge detection algorithms of Sobel and Canny can not only effectively eliminate the influence of noise on edge detection, but quickly detect the complete image edge.