Infrared small target detection based on the self-information map

The achievement of high detection probability and low false alarm probability is a bottleneck problem in the detection of infrared small targets. Thus, a new small target detection approach which integrates the concept of self-information map (SINM) with the adaptive thresholding method followed by a region growing technique is proposed in this paper. The concepts of local signal-to-noise ratio, region nonuniformity, detection probability, and false alarm probability are used to evaluate the performance. The experiment results obtained from qualitative and quantitative comparisons testify to the robustness of the approach presented under different conditions.