Infrared Small Target Detection Using Multiscale Gray and Variance Difference

Infrared small target detection plays an important role in infrared monitoring and early warning systems. This paper proposes a local adaptive contrast measure for robust infrared small target detection using gray and variance difference. First, a size-adaptive gray-level target enhancement process is performed. Then, an improved multiscale variance difference method is proposed for target enhancement and cloud clutter removal. To demonstrate the effectiveness of the proposed approach, a test dataset consisting of two infrared image sequences with different backgrounds was collected. Experiments on the test dataset demonstrate that the proposed infrared small target detection method can achieve better detection performance than the state-of-the-art approaches.