Edge Detection Using Multispectral Thresholding

Edge detection is a fundamental tool in image processing and computer vision, particularly in the areas of feature detection and extraction. Among various edge detection methods, Otsu method is one of the best optimal thresholding methods for general real world images with regard to uniformity and shape measures. In this paper, a multispectral thresholding algorithm using Otsu method is proposed to detect the edges in multispectral images. Natural, art and simulated images are considered for testing. Since the edges are well known in the simulated images, they are considered for performance evaluation. The results of proposed method, Edge Detection using MultiSpectral Thresholding (EDMST), are compared against the results of Canny Otsu, Improved Otsu, Median based Otsu and Improved Gray Image Otsu edge detection algorithms based on the human visual system, the number of edges and the number of pixels. The experimental results show that the proposed method achieves better performance and hence applied on Satellite images.