Real-time image registration of the multi-detectors mosaic imaging system

According to the detector arrays mosaic imaging system designed with four lenses based on concentric spherical lens, its applied algorithms about the image registration is investigated, such as feature detection and extraction, feature vector matching and screening, spatial transformation model and parameter estimation, <em>etc</em>. First, the fast-hessian detection algorithm is used to find features, and generate feature vector of SURF descriptors. Second, the fast approximate nearest neighbor search algorithm is used to obtain the initial matching points and to sort the Euclidean distance between feature vectors in the matching points. Then after screening the feature points, the good ones are preserved based on a reasonable threshold interval from the optical design parameters. Finally, the transform parameters are estimated by using the improved progressive sample consensus method and the spatial geometry transformation relationship is obtained about the reference image and registration image. Experimental results indicate that the algorithm has some invariance about the size, rotation and illumination changes; the feature matching time is 0.542 s, and the registration transform time is 0.031 s; the registration error precision is less than 0.1 pixel, which can meet the requirements of the imaging system about the image registration including good real-time and accuracy performance.