grid clustering in detection image via target prior information

For synthetic aperture radar (SAR) images, the key to successful automatic target recognition is accurate extraction of regions of interests(ROI), and as a consequence, the clustering algorithm is the key to ROI extraction. A novel approach based on grid clustering is propose in this paper, which can significantly reduce the false alarm rate and the computational complexity. Firstly, the statistics of geometrical features are gathered to determine the parameters of the algorithm; then, the whole duty ratio map is generated by computing the duty ratio in each grid, and the oversized and undersized clutters is discarded according to the corresponding duty ratios; at last, the ROI centers are estimated from the duty ratio map. The feasibility and effectiveness of our proposed approach are demonstrated by simulation and real experimental results.