Single frame infrared small target detection based on local gradient and directional curvature

Infrared (IR) small target detection in a single frame is a challenging task due to the lack of texture and color information and the interference of background clutters. In light of the two-dimensional Gaussian-like shape of IR small target, two properties from the perspective of local gradient and directional curvature (LGDC) are characterized. Specifically speaking, the local gradients in four quadrants as well as the curvatures from four directions should distribute in a regular way in the target region. Therefore, an LGDC map is computed from the input IR image so that the contrast between target and background can be greatly improved. By this means, we are able to extract the IR small target by a simple threshold related to the mean and standard deviation values of the LGDC map. Experiments implemented on real IR images verify that the proposed method can achieve satisfactory performance in terms of local contrast enhancement and background clutter suppression.