Detection of small infrared targets based on multi-feature fusion

A novel method for small weak target detection based on multi -feature distance map (MFDM) in image sequences is proposed. Small weak targets have many features like local entropy, average gradient strength etc. These features not only describe the characteristics of small infrared targets, but also are easy to be extracted. Multi-feature-based fusion techniques are applied to detect weak targets by converting the problem of detecting small targets to the search for peak values in specified feature space where multi -feature vectors space (MFVS) is considered. Target detection is performed in DM which can be derived according to feature vectors. The targets are detected in complex backgrounds via binarizing a DM image constructed by multi -feature fusion. The proposed approach is validated using actual infrared image sequences with sea-sky backgrounds. Experimental results demonstrate the robustness and high performance of the proposed method.