Infrared small target detection with complex background based on image layer and confidence analysis

An image layering and confidence analysis based small target detection method in infrared image is proposed. First, a Huffman tree is used to refine the histogram curve, and the valleys of the refined curve are detected automatically. Then, the grey values of the detected valleys are recorded as the segmenting thresholds to stratify the original infrared image. After detecting small abnormal regions in each layer and defining them to be candidate targets, the candidate target set is composed of the candidate targets in all layers. Finally, the abnormality based confidence of each candidate target is calculated and sorted. The candidate target with maximum confidence is considered as the real one. The experiments show that the proposed method performs robustly and efficiently.