采用轮廓特征匹配的红外-可见光视频自动配准

To register infrared-visible video sequences precisely inalmost-planar scenes, an automatic registration method based on matching the contour features was proposed in this paper. This method could solve the challenging problem regarding extracting and matching features in multimodal images by iteratively matching the contour features of targets. First, this method adopted the technology of moving target detection to identify the contours of targets and extracted the contour feature points with the corner detection algorithm of Curvature Scale Space(CSS). Then, the global shape context descriptors and the local histogram of edge orientation descriptors were established to describe the features; theseareuseful forreliable feature matching. The matched feature pairs from different times were reserved in a reservoir based on the Gaussian distance criterion. Finally, to overcome the influence of target depth variationin almost-planar scenes, the loss function of the registration matrix was calculated by incorporating the strategy of randomly sampling foreground samples, after which the global registration matrix was updated. The method was validated using the LITIV dataset, and the results demonstrate that the proposed method outperforms state-of-the-art methods. The average overlap error of our method on nine test sequences is only 0.194; this value for the compared methods demonstrate a decrease of 18.5%. This essentially satisfies the precise requirement of infrared-visible video registration in almost-planar scenes, and this method is fairly robust.