A modular clutter rejection technique for FLIR imagery using region-based principal component analysis

In this paper(1), a modular clutter rejection technique using region-based principal component analysis (PCA) is proposed. Our modular clutter rejection system uses dynamic ROI extraction to overcome the problem of poorly centered targets. In dynamic ROI extraction, a representative ROI is moved in several directions with respect to the center of the potential target image to extract a number of ROIs. Each module in the proposed system applies region-based PCA to generate the feature vectors, which are subsequently used to decide about the identity of the potential target. We also present experimental results using real-life data evaluating and comparing the performance of the clutter rejection systems with static and dynamic ROI extraction.