A Side Scan Sonar Image Target Detection Algorithm Based on a Neutrosophic Set and Diffusion Maps

To accurately achieve side scan sonar (SSS) image target detection, a novel target detection algorithm based on a neutrosophic set (NS) and diffusion maps (DMs) is proposed in this paper. Firstly, the neutrosophic subset images were obtained by transforming the input SSS image into the NS domain. Secondly, the shadowed areas of the SSS image were detected using the single gray value threshold method before the diffusion map was calculated. Lastly, based on the diffusion map, the target areas were detected using the improved target scoring equation defined by the diffusion distance and texture feature. The experiments using SSS images of single clear and unclear targets, with or without shadowed areas, showed that the algorithm accurately detects targets. Experiments using SSS images of multiple targets, with or without shadowed areas, showed that no false or missing detections occurred. The target areas were also accurately detected in SSS images with complex features such as sand wave terrain. The accuracy and effectiveness of the proposed algorithm were assessed.