Image registration is a difficult problem when dealing with images captured by different sensors, for instance, Visible and IR sensors, due to their texture, gray not matched and feature inconsistent. Since the edges of the objects present in the images are preserved in most cases, so, in this paper, a new contour-based image registration algorithm is proposed. First, an edge detection method based on multi-scale and multi-direction morphology is proposed for extracting contour. Then the matched contour pairs are found according to the following shape attributes, such as the first and second invariant moments, etc. Next, within these matched contours, several control-point pairs are selected, which has the characteristics of 1) even distribution 2) a suitable number of points 3) locally maximum curvature. In addition, the sea-sky-line is extracted in advance, which determines the region of image registration and reduces the computation time. The performance of our algorithm is demonstrated by estimating the registration accuracy and evaluating the fusion effects of the visual and IR images of ship target.
IR and visible sensors are very common sensors adopted in the region of military image fusion, however, since there are less correlation and lack of consistent features between their acquired images, it is very difficult to achieve automatic registration of IR and visible images. In this paper, optoelectronic imaging anti-ship missile is taken as research object, and based on the analysis of its seeker's imaging process, we proposed a new automatic registration algorithm based on sensor parameters and image information. The basic idea of our algorithm is that decomposing the transform model, and simplifying it step by step. For example, the transform of IR and visible image registration is affine. By adjusting sensor parameters, the affine transform can be simplified to rigid transform through eliminating the scaling change between images, and by finding out the centroid of ship target's contour we can further eliminate the translational change between them. After image registration is achieved, the registration effect is assessed by judging whether the sea-sky-lines of the two registered images are in the same position. The final simulation experiments convince us that our algorithm has better performance on solving the difficult registration problem of small target images with different sensors.