Edge Detection for SAR Images Using ACO

Detecting Edge in Synthetic aperture radar (SAR) imagery is to extract contours across the investigated SAR image. Classical edge detection methods provide a limited efficiency in SAR imagery for the presence of speckle noise. Ant colony optimization (ACO) is an optimization algorithm inspired by the natural behavior of ant species that ants deposit pheromone on the surface of the ground for foraging. In this paper, ACO is used to examine edge detection for SAR images. The proposed ACO-based edge detection approach is able to establish a pheromone matrix that represents the edge information presented at each pixel position of the image, according to the movements of a number of ants which are dispatched to move on the image. Furthermore, the movements of these ants are driven by the local variation of the image's intensity values. Experimental results are provided to illustrate the superior performance of the proposed approach.

Keywords:

Image processing , Synthetic Aperture Radar , Edge Detection , Ant Colony Optimization