Small Target Detection in Infrared Videos Based on Spatiooral Tensor Model

Existing methods of the small target detection from infrared videos are not effective with the complex background. It is mainly caused by: 1) the interference of strong edges and the similarity with other nontarget objects and 2) the lack of the context information of both the background and the target in a spatiooral domain. By considering these two points, we propose to slide a window in a single frame and form a spatiooral cube with the current frame patch and other frame patches in the spatiooral domain. Then, we establish a spatiooral tensor model based on these patches. According to the sparse prior of the target and the local correlation of the background, the separation of the target and the background can be cast as a low rank and sparse tensor decomposition problem. The target is obtained from the sparse tensor by the tensor decomposition. The experiments show that our method gains better detection performance in infrared videos with the complex background by making full use of the spatiooral context information.