New multispectral edge detection methods based on roughness and differential Prewitt

In this paper, two new edge detection methods for multi-spectral images are presented. The first method is based on calculating Euclidean distances between pixel vectors inside a suitable mask. This method approximates the roughness of the pixel neighborhood. The result is a scalar edge image. This method is tested using an airborne remote sensing image and two artificial images. One artificial image contains metamerie colors and the other have group of colors arrnged using the Self Organizing Map. In all the cases, the edges are clearly visible without further filtering. The second method is a differential Prewitt method using vectors for calculating the gradient value. In this case the edge image is a vector image. This method is tested using the same test images as in the first case.