A Fusion of Target Detection Method from SAR Image and Optical Image

A new targets detection method is proposed in this paper, which take advantage of the composite properties of targets in synthetic aperture radar(SAR) image and optical image, based on that military targets have strong radar cross section(RCS), strong back scattering characteristics and easy to detect in SAR images and the targets in the optical images have good geometry features and easy to distinguish the targets from background. There are three steps about the approved method: images preprocessing, target detection and data fusion on features. At first, the images from multisensor are registered with featurebased registration algorithm. The second, the global Constant False Alarm Rate(CFAR) algorithm is used to detect by targets in SAR images, after filtering processing, the Regions of Interest(ROI) are obtained in SAR image. Mapping the ROIs to optical image, the edge features and characteristics of connected areas of targets are extracted in the ROIs of optical images. Finally, the distance of feature vectors is used to detect targets on feature level. The experimental result shows this algorithm has better performance than detection algorithm on single sensor.