A multifeature-based algorithm for small target detection

In this paper, an efficient algorithm of small target detection has been developed which combines the geometric properties of low-order moments of specific targets with the signature of discontinuity not widely used in current methods between small targets and its neighbor regions. This algorithm includes two steps: 1) to construct an average grey absolute difference maximum map (AGADMM), eliminate the background clutter and then enhance the target; and 2) to use the geometric properties of low-order moments of a specified target to discriminate between the targets and other normal objects. Experiments with visual and infrared images has shown that this algorithm can provide satisfactory detection performance for exploiting many features of a specified target in detecting a small target.