Multi-Target Infrared–Visible Image Sequence Registration via Robust Tracking

To solve the problem of multi-target depth difference for infrared and visible image sequence registration, a registration framework based on robust tracking is proposed. Firstly, the curvature scale space corners of targets are extracted, and the descriptors based on the curvature distribution are created to complete feature matching. Since different targets lie on different depth planes, single global transformation matrix is no longer applicable. Robust target tracking algorithm is introduced to dynamically allocate and update the matching reservoir for each target. Finally, the precise registration of multiple targets is realized by computing transformation matrix independently for each target. Experiments on a public dataset of non-planar infrared and visible image sequences show that our framework achieves lower overlapping errors and improves the accuracy of multi-target registration.