An Infrared small target detection method based on local contrast measure and gradient property

Infrared small target detection plays an important role in infrared search and tracking applications. In order to solve the problem of detection has high false alarm rates and low probabilities with complex backgrounds. An infrared small target detection method based on local contrast measure and gradient property (LCG) is proposed in this paper. Initially, the contrast map of the input image is calculated using the modified local contrast measure which is employed to enhance target and suppress background. Then, according to the property of distribution regularly around the target, the gradient map is calculated from the input image to further suppress clutters. Next, the feature map is achieved by integrating the local contrast map and gradient map in a pixel-wise multiplication manner. Finally, an adaptive threshold is used to extract the target region. Experimental results on two real sequences demonstrate that the proposed method has a good performance in background suppression and target enhancement. Besides, the proposed method has satisfying robustness under complex backgrounds. (paper)