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GIS-assisted image registration for an onboard IRST of a land vehicle

The target detection can be carried out with a statistical matched filter. The construction of the matched filter needs the information on the background clutter statistics as well as on the shape of the target. For the computational simplicity, a filter bank consisted with pre-designed matched filters can be used for adaptive filtering. The classification of background clutter must be preceded to compose a filter bank and need pre-collection of samples of background clutter. In land-based IRST, there are too many different types of background clutter to hold a filter bank tuned to them. To overcome this difficulty, we propose a new classification method which use GIS (Geographic Information Science) -assisted background registration. We discern different clutter regions in the initial image frame using a feature vector composed of the vertical and the horizontal autocorrelation and build filters tuned to each class. In the successive frames, we classify each region of different clutter from contour image obtained by projecting the GIS data and by registering to the previous image. Each classified region of image is then filtered using a pre-designed matched filter in the previous image frame. We only have to construct a filter for newly appeared region. The proposed algorithm has been tested with synthetic image frames, and we observe that our method has advantages of reducing computational load and false detection at edges.