The existing thermal infrared (TIR) ship detection methods may suffer serious performance degradation in the situation of heavy sea clutter. To cope with this problem, a novel ship detection method based on morphological reconstruction and multi-feature analysis is proposed in this paper. Firstly, the TIR image is processed by opening- or closing-based gray-level morphological reconstruction (GMR) to smooth intricate background clutter while maintaining the intensity, shape, and contour features of ship target. Then, considering the intensity and contrast features, the fused saliency detection strategy including intensity foreground saliency map (IFSM) and brightness contrast saliency map (BCSM) is presented to highlight potential ship targets and suppress sea clutter. After that, an effective contour descriptor namely average eigenvalue measure of structure tensor (STAEM) is designed to characterize candidate ship targets, and the statistical shape knowledge is introduced to identify true ship targets from residual non-ship targets. Finally, the dual method is adopted to simultaneously detect both bright and dark ship targets in TIR image. Extensive experiments show that the proposed method outperforms the compared state-of-the-art methods, especially for infrared images with intricate sea clutter. Moreover, the proposed method can work stably for ship target with unknown brightness, variable quantities, sizes, and shapes.
The existing infrared (IR) ship target segmentation methods may suffer serious performance degradation in the situation of diverse background clutters and ship targets. To cope with this problem, a novel ship target segmentation method is proposed in this paper. Initially, the IR image is transformed into the map of large eigenvalues of structure tensor (STLE), where the horizon line and ship target boundary can be explicitly characterized. According to the scene context clue, the automatic horizon line detection (AHLD) is proposed to efficiently judge the existence of horizon line and remove sky/land region clutters. Then, based on the intensity distribution of ship target and sea background, the adaptive maximum histogram entropy (AMHE) is presented to accurately perceive the brightness (dark or bright) of ship target, and coarsely segment the bright or dark ship target from sea background. After that, considering the ship target boundary information, the regions-of-interest (ROI) of ship target is located and the ship foreground map (SFM) is developed to address the under-segmentation. Finally, a new Watershed algorithm namely structure tensor and maximum histogram entropy modified Watershed transform (TEWT) is constructed to completely extract the whole ship target. Extensive experiments show that the proposed method outperforms the state-of-the-art methods, especially for IR images with intricate background clutter and heavy noise. Moreover, the proposed method can work stably for ship target with unknown brightness, uneven intensities, low contrast, variable quantities, sizes, and shapes.INDEX TERMS Infrared (IR) imaging, ship target segmentation, structure tensor, maximum histogram entropy, modified watershed transform.
The rockburst disaster in the hard rock caused by excavation and unloading of deep underground caverns threatens the safety of engineering construction. In recent years, the microseismic monitoring technology, which can dynamically monitor the whole process of progressive failure of rock mass in real time, has been widely used in rockburst monitoring and early warning of underground engineering. In view of the slight rockburst in local surrounding rock during the excavation of underground powerhouse of Huanggou Pumped Storage Power Station, a rockburst microseismic monitoring system is constructed. And through the analysis of the temporal and spatial activity of microseisms during the monitoring period, the potential risk areas of rockbursts are identified and delineated. The monitoring results show that the microseismic system can effectively capture the blasting and microseismic signals during construction. The microseismic activity is closely related to the intensity of field blasting disturbance. The potential risk areas of rockburst are the upstream side arch shoulder and the intersection between lower drainage corridor and workshop installation room. The research results can provide technical support for later excavation and support of underground powerhouse caverns of Huanggou Hydropower Station.
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