Area Ratio Invariant Feature Group for Ship Detection in SAR Imagery

Abstract

Standard deviation (SD) is one of the most famous features for image processing. It is widely used for ship detection in synthetic aperture radar imagery. However, it is very sensitive to the area ratio of target. It cannot reflect intensity fluctuation appropriately in some cases. Traditional constant false alarm rate (CFAR) detectors, e.g., cell-averaging CFAR, fail in dense target situations. This paper shows that this classical problem can be understood as a same problem in terms of area ratio variant and area ratio invariant (ARI). It reinterprets the reason for CFAR performance degradation and provides new insight into this problem. This paper begins with the proposal of an ARI-SD feature. Then, ARI-feature group (ARI-FG) is defined. Finally, traditional CFAR detectors are modified by ARI-FG. Compared to traditional features, the proposed ARI features are independent of the area ratio, by means of an elimination of the influence from area variation. Experimental results based on real data show that the modified CFAR method does not cause detection loss and additional false alarms compared to traditional CFAR. It is more effective and robust in dense target situations. In addition, the potential of ARI-FG for ship discrimination is also explored in this paper.