Small Infrared Maritime Target Detection Based on Gradient Amplitude Difference and Multidimensional Dissimilarity Measure

Infrared target detection is a key technology in maritime distress target search and tracking systems. Particularly, detecting small targets overwhelmed in heavy waves is an important and challenging task. In order to effectively enhance small infrared maritime target saliency and suppress heavy wave clutter, a small infrared maritime target detection method based on gradient amplitude difference and multidimensional dissimilarity measure is proposed in this paper. Firstly, we employ Sobel operator to measure the gradient amplitude difference (GAD) by calculating minimum component of gradient between horizontal and vertical directions. Meanwhile, we use facet kernel filtering followed by adaptive threshold segmentation to extract the sizes, shapes, and locations of candidate targets; then, multidimensional dissimilarity information, i.e. multi-direction and multi-scale, is constructed based on original infrared image and locations of candidate targets. Multidimensional dissimilarity measure (MDM) achieves target enhancement and background clutter suppression. The final saliency map is obtained by multiplying GAD and MDM. Finally, an adaptive threshold is used to segment targets from residual interferences. Experimental results on three real infrared maritime image sequences show that, the proposed method achieves better performance in terms of local contrast gain, background suppression factor, and detection probability with low false alarm. Our method performs more satisfactorily and robustly than the state-of-the-art methods.