Morphological edge detection algorithm based on hierarchical multi-scale

Remote sensing image combines the characteristics of visible light image, infrared image and other multi-spectral images, making it rich in details and low resolution. However, due to factors such as weather and transmission errors, salt and pepper noise is prone to occur, and it is difficult to effectively detect weak edges. Aiming at the problems, a morphological edge detection algorithm based on hierarchical multi-scale is proposed in this paper. Firstly, the adaptive median filter is used to smooth the remote sensing image. Secondly, it is proposed to use the mutual information of images as the cost function for processing, and the multi-scale hierarchical ratio is 2 1 . Then, the four directional structural elements of 0 , 45 , 90 and  135 are used to extract the original-scale and small-scale image edges respectively. Calculate the sum of the gray difference values of eight neighborhoods of the edge points, thus calculate the direction adaptive weight, and then the edge detection results are obtained by fusion respectively. Finally, the pixels in the edge image are classified, and the fusion method of enhancing edge and weak edge and filtering false edge is proposed, and then the edge detection image is obtained. Aiming at the application of remote sensing images, the comparison of the results shows that the proposed algorithm has stronger anti-noise performance, the weak edge detection ability is improved, thus avoiding missed detection and false detection of edge information, and detecting more complete and accurate edge details.