Abstract: This paper describes a morphology-based hierarchical process for the detection and segmentation of low and high contrast targets in second generation FLIR imagery. The computational framework is based on the application of simple non-linear binary and grayscale operations that lead to real-time implementations. The process consists of two major processing steps: target-cueing/coarse- segmentation and contour refinement. Our multi-stage detection/segmentation process was applied to both real and simulated FLIR imagery. Preliminary results indicate that the developed morphology- based detector exhibits excellent detection performance for both low and high contrast targets in complex backgrounds while maintaining a low false alarm rate. Contour refinement is based on the watershed transform that is applied in a hierarchical fashion. In addition, our segmenter extracted accurate target outlines under poor conditions in which edge-based techniques or traditional watershed algorithms would have failed. !10
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