关键词: 图像分割, 边缘检测, 引导滤波, Canny算子

Abstract: In the image segmentation algorithm based on edge features, it is the premise and key to accurately detect the edge. Aiming at the shortcomings of remote sensing image segmentation algorithms, such as poor robustness, easy edge information loss and narrow application range, this paper proposes a remote sensing image segmentation algorithm based on improved Canny edge detection. For the traditional Canny Gaussian filter, the image is smoothed while smoothing the image, and the image is smoothed by the guidance filtering with the edge-preserving property. For the problem that the noise is sensitive to the derivative, the gradient template is added to calculate the image gradient and direction. For the limitation of setting the high and low thresholds by the traditional Canny operator, the Ostu algorithm is used to adaptively select the high and low thresholds according to the gray level of the image. In order to make full use of the advantages of multi-spectral images, band decomposition is performed in the edge detection, and processing is performed on a band-by-band basis, and then the edges are integrated into a result image, and finally region growth is performed. The experimental results show that compared with the traditional detection edge segmentation method, the proposed method achieves good results in remote sensing image segmentation.

Key words: image segmentation, edge detection, guided filter, Canny